Cyber Security Engineer Jobs in Egypt

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Provide support and guidance to the sales team in all aspects of sales operations, including quoting, proposal creation, order management, and contract administration. Manage and maintain CRM system data, ensuring accuracy and completeness. Analyze sales data and metrics to identify trends, opportunities, and areas for improvement. Collaborate with cross-functional teams, including finance, marketing, and operations, to ensure alignment and efficiency in sales processes. Develop and implement sales policies, procedures, and guidelines to improve sales productivity and effectiveness. Create and deliver sales performance reports and dashboards to provide insights and support decision-making. Assist in developing and managing sales incentive programs to motivate and reward the sales team. Support the sales team in lead generation and qualification activities. Provide training and onboarding to new sales team members on sales processes and systems. Stay updated on industry trends and best practices in sales operations and recommend improvements accordingly.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"><b>Qualifications:</b></p><p>Bachelor's degree in Business Administration, Marketing, Engineer or a related field. Minimum of 5 years of experience in sales operations or a related field. Strong analytical and problem-solving skills with the ability to work with large sets of data. Proficiency in CRM systems and sales reporting tools. Strong attention to detail and excellent organizational skills. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams. Ability to multitask and prioritize effectively in a fast-paced environment. Experience in the technology industry is preferred.</p><p></p></section>

Staff Data Engineer<br>About the Role Intellias is looking for a Staff Data Engineer to join a large-scale digital healthcare initiative focused on building the data and AI foundations that power personalized healthcare experiences. This is a Staff-level Individual Contributor role for an engineer who combines deep data engineering expertise with distributed systems thinking, backend development, and technical leadership. You will design and build scalable data infrastructure, solve complex cross-platform engineering challenges, and establish technical patterns and standards adopted across multiple engineering teams. The role is highly hands-on while also requiring the ability to provide technical direction, mentor experienced engineers, and influence architecture across the broader platform.<br>Project Overview The project is building a FHIR-based healthcare data platform that integrates data from EHRs, healthcare applications, wearables, portals, and other sources to enable connected and personalized healthcare experiences. The platform supports:Real-time and batch data processing Operational and analytical workloads Healthcare interoperability Data-intensive product capabilities Machine learning and AI use cases Scalable, cloud-native data infrastructure<br>The technology landscape includes Python, PySpark, Apache Spark, Kafka, Duck DB, Prefect/Airflow, Fast API, Mongo DB, Docker, Kubernetes, and cloud-native infrastructure. The core engineering challenge is to build secure, reliable, and scalable data foundations capable of processing heterogeneous healthcare data while supporting product engineering, analytics, machine learning, and emerging AI capabilities.<br>What You’ll DoDesign and implement solutions for large-scale, ambiguous data engineering and distributed-systems challenges. Architect, build, and evolve real-time and batch data infrastructure supporting operational, analytical, and AI/ML workloads. Design and scale event-driven data pipelines using technologies such as Kafka, Spark, and PySpark. Build production backend services and APIs using Python and Fast API to support data and platform capabilities. Define scalable approaches to data ingestion, transformation, modeling, validation, storage, and delivery. Design data architectures that address schema evolution, data quality, heterogeneous data integration, scalability, and operational reliability. Establish and champion technical standards, architectural patterns, engineering best practices, and reusable platform components. Serve as a cross-team technical authority for data systems, distributed processing, pipelines, and platform architecture. Improve the reliability, scalability, performance, and cost efficiency of data infrastructure. Implement robust observability, logging, monitoring, and alerting across distributed data systems. Design systems with security, privacy, healthcare compliance, and scalability built in from the beginning. Improve engineering workflows, CI/CD pipelines, automated testing, and production deployment practices. Collaborate closely with Product, ML/AI, Platform, Infrastructure, and application engineering teams to develop shared data capabilities. Provide technical mentorship through architecture reviews, design discussions, pairing, and knowledge sharing. Evaluate emerging data and AI technologies and introduce them where they provide measurable improvements to platform capabilities or engineering efficiency. Remain hands-on with production engineering, validating architectural decisions through implementation and operational experience.<br>What You Bring Required Qualifications8+ years of professional software and data engineering experience, including at least 3 years working with large-scale distributed data systems. Deep expertise designing and building scalable data platforms, pipelines, and distributed processing systems. Strong hands-on proficiency in Python, with production experience using technologies and libraries such as PySpark, Pandas, and Fast API. Strong experience with Apache Spark/PySpark and distributed data processing at scale. Experience designing and implementing real-time and batch data pipelines using Kafka, Spark, or comparable distributed processing technologies. Strong understanding of data architecture, data modeling, schema evolution, data quality, and heterogeneous data integration. Experience with workflow orchestration technologies such as Prefect, Apache Airflow, or equivalent. Experience building production backend services and APIs supporting data and platform capabilities. Strong SQL skills and hands-on experience with modern data storage technologies, including relational and NoSQL databases such as Mongo DB. Strong understanding of distributed systems principles, including scalability, reliability, fault tolerance, consistency, and performance. Experience designing and implementing observability, logging, monitoring, and alerting for distributed data systems. Strong cloud-native engineering experience, including Docker, Kubernetes, CI/CD, and production deployment practices. Proven ability to independently design solutions for ambiguous, large-scale engineering problems spanning multiple systems and teams. Demonstrated experience establishing technical standards, engineering patterns, development practices, and reusable platform capabilities. Strong technical leadership skills, including experience mentoring senior engineers, conducting design reviews, and influencing architecture without formal people-management authority. Strong understanding of security, privacy, and data protection principles for production data platforms. Professional English proficiency sufficient for direct collaboration with U. S.-based engineering, product, ML, and platform teams. Bachelor's degree in computer science, Engineering, or a related field.<br>Nice to Have Experience with FHIR, HL7, C-CDA, or other healthcare interoperability standards. Previous experience in healthcare, Health Tech, or another regulated data environment. Understanding of HIPAA, HITECH, or comparable data privacy and compliance requirements. Experience deploying or supporting LLMs, ML models, AI-enabled data products, or retrieval-based systems. Experience building data infrastructure supporting ML/AI workloads and production inference. Hands-on experience with observability technologies such as Open Telemetry, Datadog, Prometheus, or similar platforms. Experience with Duck DB or modern analytical data-processing technologies. Experience with AI-assisted engineering tools such as Claude Code, Git Hub Copilot, Cursor, or comparable solutions. Contributions to open-source projects or publicly available engineering initiatives.<br>Why Join This Initiative? This role offers the opportunity to shape the data and AI foundations of a modern healthcare platform operating at significant scale. You will work on technically complex challenges spanning:Distributed data processing Event-driven architectures Backend services Cloud-native infrastructure Healthcare interoperability Data platform architecture AI/ML enablement<br>As a Staff-level Individual Contributor, your impact will extend well beyond individual services or pipelines. You will establish architectural patterns, influence technical decisions across teams, mentor experienced engineers, and help define how the broader engineering organization builds and operates data-intensive systems. At the same time, this is fundamentally a hands-on engineering role. You will design systems, build critical components, validate architectural decisions through code, and remain closely connected to how systems behave in production. This position is particularly well suited for an engineer who wants to combine deep technical expertise with organization-wide engineering influence while building data infrastructure that directly enables better healthcare products and emerging AI capabilities.

Senior Python Engineer – Multi-Agent AI (AWS, Lang Graph)<br>About the Role We are looking for a Senior Python Engineer to design and build enterprise-grade multi-agent AI systems on AWS. In this role, you will architect and develop intelligent agent solutions using Lang Graph, Lang Chain, and AWS Bedrock Agent Core Runtime, focusing on scalable orchestration, stateful workflow execution, human-in-the-loop (HITL) processes, and distributed agent collaboration. You will work closely with architects, platform engineers, and product teams to deliver production-ready AI solutions that are reliable, scalable, and aligned with enterprise engineering standards.<br>Project Overview Our customer is a multinational corporation with more than a century of history and operations in over 180 countries. One of its key strategic initiatives is the development and adoption of a new generation of Reduced-Risk Products (RRPs), targeting more than one billion consumers worldwide. Intellia partners with the customer to engineer a comprehensive software ecosystem supporting innovative IoT products, digital commerce, and enterprise platforms. The engineering organization develops core platform components powering best-in-class e Commerce, Digital Marketing, and IoT solutions. As a Senior Python Engineer, you will join the Core Architecture Team, contributing to the design and implementation of a modern Digital Engineering Enterprise Platform. The platform consists of services and applications that accelerate software delivery by providing engineering teams with reusable technologies, standardized development practices, compliance controls, and operational capabilities across more than 700 enterprise applications.<br>Responsibilities Design, develop, and maintain enterprise-grade multi-agent AI applications using Python, Lang Graph, and Lang Chain. Build scalable agent workflows leveraging AWS Bedrock Agent Core Runtime. Implement advanced orchestration patterns, including supervisor/worker, fan-out/fan-in, and collaborative multi-agent architectures. Design stateful workflow execution using Lang Graph checkpointing, recovery, and persistence mechanisms. Develop resilient, fault-tolerant, and idempotent execution strategies for long-running AI workflows. Integrate Human-in-the-Loop (HITL) approval processes into business-critical agent workflows. Enable agent delegation and collaboration through Agent Gateway and Agent-to-Agent (A2A) communication. Implement memory, context management, and persistence strategies for AI agents. Optimize workflow scalability, reliability, observability, and performance within distributed cloud environments. Collaborate with platform, security, Dev Ops, and product teams to deliver production-ready AI solutions. Define engineering standards, testing strategies, and operational best practices for agent-based applications. Support deployment, monitoring, troubleshooting, and continuous improvement of AI solutions running on AWS. Requirements Bachelor's degree in computer science, Software Engineering, or a related field.5+ years of professional Python software engineering experience. Hands-on experience building multi-step agent workflows with Lang Graph. Strong experience with Lang Chain. Experience with AWS Bedrock Agent Core Runtime. Solid understanding of multi-agent orchestration patterns, including supervisor/worker and fan-out/fan-in architectures. Experience implementing Lang Graph checkpointing and state management. Knowledge of Human-in-the-Loop (HITL) workflow design. Experience with Agent-to-Agent (A2A) delegation through Agent Gateway. Experience with workflow orchestration platforms such as Temporal, Apache Airflow, or similar. Strong understanding of distributed systems concepts, including checkpointing, idempotency, fault tolerance, and workflow recovery. Experience building scalable, cloud-native applications on AWS. Strong problem-solving, communication, and collaboration skills.<br>Nice to Have Experience evaluating AWS Agent Core Runtime maturity and enterprise adoption. Hands-on experience with AWS Bedrock Memory API. Experience integrating enterprise approval workflows into Human-in-the-Loop AI systems. Experience with AI observability, monitoring, and production operations. Familiarity with CI/CD pipelines and Infrastructure as Code in AWS environments.<br>Why Join UsWork on enterprise-scale AI initiatives for a global industry leader. Design and build next-generation multi-agent AI systems using cutting-edge AWS technologies. Influence architecture decisions and engineering best practices across large-scale platforms. Collaborate with highly experienced architecture and engineering teams on innovative cloud-native solutions. Opportunity to shape the future of enterprise AI orchestration in production environments.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: GoProficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C#Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Ruby Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: GoProficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Ruby Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Rust Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 3 month; [expected start date is next week]<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C#Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Ruby Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Rust Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 3 month; [expected start date is next week]<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C#Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: GoProficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

<p><strong>Join Our Dynamic Team as a Facility Management Engineer in Beautiful Cairo!</strong></p><p>Are you ready to take the reins of operational excellence and drive innovation in facility management? We are seeking a highly motivated and experienced <strong>Facility Management Engineer</strong> to lead the charge in optimizing our physical assets and ensuring a seamless, efficient, and safe environment. This is an incredible opportunity to leave your mark in a vibrant, on-site role in Cairo, Egypt.</p><p><strong>About the Role:</strong></p><ul><li><strong>Overview:</strong> As our Facility Management Engineer, you will be the cornerstone of our operational success, blending your engineering prowess with strategic facility oversight. You'll be instrumental in maintaining, improving, and managing our infrastructure, ensuring everything runs like a well-oiled machine.</li><li><strong>Responsibilities:</strong></li><ul><li>Oversee and manage all aspects of facility operations, including mechanical, electrical, civil, and architectural systems.</li><li>Develop and implement robust maintenance and repair programs to ensure optimal functionality and longevity of assets.</li><li>Lead and execute diverse engineering projects, from minor upgrades to significant infrastructure enhancements, ensuring timely and budget-compliant delivery.</li><li>Leverage Information Technology (IT) solutions to streamline facility management processes, enhance reporting, and improve decision-making.</li><li>Conduct regular inspections and assessments to identify potential issues and proactively implement corrective measures.</li><li>Manage vendor relationships and service contracts, ensuring high-quality and cost-effective solutions.</li><li>Ensure strict adherence to all health, safety, and environmental regulations and best practices.</li></ul><li><strong>Skills & Technologies:</strong> You will thrive by utilizing your expertise in various engineering disciplines, project management methodologies, and facility management software. A strong grasp of IT principles applied to operational efficiency will be key to your success.</li><li><strong>Growth Opportunities:</strong> This role offers significant potential for professional advancement. You'll gain invaluable experience in a critical leadership position, with pathways to senior management roles and the opportunity to specialize further in areas like sustainable facilities or advanced building technologies.</li><li><strong>Team & Culture:</strong> You'll be part of a collaborative and forward-thinking team committed to excellence. We foster a culture of continuous improvement, innovation, and mutual support, where your contributions are valued and celebrated.</li><li><strong>Impact:</strong> Your work will directly contribute to the productivity, safety, and overall success of our operations. You will be a critical player in maintaining a world-class environment for our employees and stakeholders.</li></ul><p><strong>Requirements</strong></p><ul><li><p><strong>Experience That Excites Us:</strong></p><ul><li><p>A minimum of <strong>3-7 years of hands-on experience</strong> in Facility Management, Engineering (Mechanical, Electrical, Civil, or Construction), or a related field.</p></li><li><p>Proven track record of successfully managing complex projects and leading maintenance operations.</p></li></ul></li><li><p><strong>Skills You'll Bring to the Table:</strong></p><ul><li><p><strong>Exceptional proficiency in Engineering principles</strong> across mechanical, electrical, and civil disciplines.</p></li><li><p><strong>Demonstrated expertise in Facility Management</strong> best practices, including preventive and corrective maintenance.</p></li><li><p><strong>Strong capabilities in Project Management</strong>, with a history of delivering projects on time and within budget.</p></li><li><p>A solid understanding of <strong>Information Technology (IT)</strong> applications relevant to facility operations and management systems.</p></li><li><p>Proficiency in using tools like <strong>AutoCAD</strong> for design and documentation.</p></li><li><p>Experience with <strong>Building Systems</strong>, including HVAC, plumbing, Fit out and electrical infrastructure.</p></li><li><p>Adept at <strong>Risk Management</strong> and implementing safety protocols.</p></li><li><p>Excellent skills in <strong>Vendor Management</strong> and contract negotiation.</p></li><li><p>Proven ability in <strong>Budgeting</strong> and financial oversight for facility operations.</p></li><li><p>Outstanding <strong>Problem-Solving</strong> abilities and a proactive approach to challenges.</p></li></ul></li><li><p><strong>Career Level Expectations:</strong></p><ul><li><p>This role is perfect for an <strong>Experienced</strong> professional eager to take on significant responsibility and make a tangible impact.</p></li></ul></li></ul><p></p>

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C#Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Rust Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 3 month; [expected start date is next week]<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: Ruby Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C#Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.<br>About the Role:We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality<br>Why Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.<br>What does day-to-day look like:Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.<br>Required Skills:Minimum 3+ years of overall experience Strong experience with at least one of the following languages: GoProficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.<br>Nice to Have:Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type: Contractor assignment (no medical/paid leave)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.