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Phi Egypt is an accomplished Egyptian engineering solutions company that has been active as a main contractor in construction, fitting out, fine finishing & furnishing for residential, commercial, medical & corporate projects, based in Cairo, Egypt.<br>Job Title:Project Engineer<br>Role Description This is a full-time on-site role for a Site Engineer in the field of retail, administrative & commercial projects, located in Cairo, Egypt.<br>Responsibilities- Conduct site supervision for different projects to ensure adherence to plans and specifications.- Align and coordinate with suppliers for project requirements.- Create and review technical office drawings.- Design and develop mood boards for project presentations.<br>Education & Experience- Bachelor’s degree in Architecture or Civil Engineering.- 1 to 3 years of experience in site supervision in the field of high end finishing ONLY.<br>Requirements-Having a car is a MUST.-East Cairo / New Cairo residents is preferred <br>Qualifications- Strong experience in Auto CAD & Microsoft Office.- ⁠Proficiency in shop drawings.- ⁠Understand project requirements.- Understand of FF&E specifications & selection.- Attention to detail.- Effective communication and teamwork skills.- Knowledge of construction industry standards and regulations.

Phi Egypt is an accomplished Egyptian engineering solutions company that has been active as a main contractor in construction, fitting out, fine finishing & furnishing for residential, commercial, medical & corporate projects, based in Cairo, Egypt.<br>Job Title:Project Engineer<br>Role Description This is a full-time on-site role for a Site Engineer in the field of retail, administrative & commercial projects, located in Cairo, Egypt.<br>Responsibilities- Conduct site supervision for different projects to ensure adherence to plans and specifications.- Align and coordinate with suppliers for project requirements.- Create and review technical office drawings.- Design and develop mood boards for project presentations.<br>Education & Experience- Bachelor’s degree in Architecture or Civil Engineering.- 1 to 3 years of experience in site supervision in the field of high end finishing ONLY.<br>Requirements- Having a car is a MUST.-East Cairo residents is a plus.<br>Qualifications- Strong experience in Auto CAD & Microsoft Office.- ⁠Proficiency in shop drawings.- ⁠Understand project requirements.- Understand of FF&E specifications & selection.- Attention to detail.- Effective communication and teamwork skills.- Knowledge of construction industry standards and regulations.

LEONI is a global provider of products, solutions and services for energy and data management in the automotive industry. The group of companies has around 86,000 employees in 21 countries and generated consolidated sales of EUR 3.9 billion in 2025.<br><br>The value chain ranges from standardized cables and special and data cables to highly complex wiring systems and related components, from development to production. As an innovation partner with distinctive development and systems expertise, we support our customers on the path to increasingly sustainable and connected mobility concepts from autonomous driving to alternative drives as well as charging systems.<br><br>Job Description<br><br>Maintain accurate supplier and article master data while supporting supplier integration initiatives including localization, consignment agreements, logistics agreements, and delivery performance evaluation Check Material Requirements Planning (MRP) results and process supplier orders while tracking deliveries, identifying bottlenecks, and escalating shortage risks Ensure optimum stock levels for raw materials, taking proactive measures to avoid and reduce excess inventory and obsolete stock Support technical changes by coordinating the ordering and timely delivery of new components Develop and maintain regular contact with suppliers, conducting regular reviews of supplier delivery performance and fostering strong business relationships Support stock-take and cycle counting processes in the plant to maintain inventory accuracy Identify and escalate supply chain risks and opportunities for continuous improvement in supplier performance and operational efficiency<br><br>Qualifications<br><br>Educational Background: Bachelor’s degree in Engineering or Supply Chain Management. Years of Experience: +3 years of experience in Strategic Sourcing, Procurement, or Material Planning within a manufacturing environment. Language: Fluent in English (both written and spoken) with excellent professional communication and reporting skills. Excel Skills: Excellent command of MS Excel (advanced formulas, data analysis, and tracking tools are mandatory). Systems: SAP experience is highly preferred (Nice-to-have). MRP Knowledge: Strong understanding of Material Requirements Planning (MRP) logic and inventory control.<br><br>Additional Information<br><br>People of all genders are always meant equally; for linguistic simplification and better readability, only the masculine form is used in the text.<br><br>LEONI processes your application data in an IT-system that is consistent across the company and uses Foreign Service providers. By sending your application, you agree to this procedure. LEONI ensures the compliance with data protection. <br><br>LEONI Wiring Systems Egypt S. A. E.

We are seeking a technical and customer-focused Security Implementation Engineer to join our growing team. This role is central to our customer success mission, responsible for the end-to-end technical integration of new clients into COGNNA's security monitoring Platform. The ideal candidate is a hands-on expert with major SIEM/Security platforms and possesses deep system administration skills across Linux, Windows, and cloud environments, enabling them to independently troubleshoot and resolve complex integration challenges.<br><br>???? Key Responsibilities<br><br>???? Client Onboarding & Implementation:<br><br>Lead the technical onboarding process for new customers, from initial kick-off to full operational status Integrate customer log sources (e.g., firewalls, servers, cloud platforms, applications) with our security data lake Develop and configure custom parsers and data connectors to ensure accurate data ingestion and normalization<br><br>????️‍♂️ System Administration & Troubleshooting:<br><br>Utilize deep expertise in Linux and Windows Server to troubleshoot agent installations, log forwarding configurations, and connectivity issues directly on customer systems Act as the primary technical resource for diagnosing and resolving complex infrastructure and OS-level issues that impede data collection Contribute to the continuous improvement of our onboarding processes, creating documentation and automation scripts to increase efficiency<br><br>???? Security Advisory & Customer Success:<br><br>Serve as a trusted technical advisor to clients during the onboarding phase, providing guidance on logging best practices and security architecture Work closely with the Security Operations Center (SOC) and account managers to ensure a seamless handover of clients upon successful onboarding<br><br>Requirements<br><br>???? Experience:<br><br>Hands-on experience in a technical cybersecurity role (e.g., SOC Engineer, SIEM Engineer, Security Consultant)3+ with direct responsibility for technical implementation or support Proven experience managing and troubleshooting both Linux (e.g., Ubuntu, Cent OS) and Windows Server environments in a production setting<br><br>???? Technical Skills:<br><br>SIEM: Expertise with major SIEM platforms. Experience with systems like Splunk, Microsoft Sentinel, Elastic Search, or Google Sec Ops is essential Operating Systems: Deep proficiency in system administration, log management, and troubleshooting across Linux and Windows Scripting: Proficiency in at least one scripting language (e.g., Python, Bash, Power Shell) for automation and parsing Security Concepts: Strong knowledge of network security architecture, cloud security (AWS, Azure, GCP), and security devices (Firewalls, IDS/IPS, EDR) Google Cloud and management of Google Sec Ops experience<br><br>???? Soft Skills:<br><br>Exceptional problem-solving skills with the ability to work independently Strong communication and interpersonal skills, with an ability to articulate technical concepts to diverse audiences A proactive, detail-oriented, and self-motivated work ethic<br><br>Benefits<br><br>???? Impact that Matters - Build products that shape the future of cybersecurity and protect organizations globally.<br><br>???? Continuous Growth - Access to certifications, trainings, and opportunities to sharpen your expertise.<br><br>???? Ownership Mindset - Benefit from our benefits program and grow with COGNNA's success.<br><br>???? Culture of Trust - We empower talent, encourage ownership, and celebrate real outcomes.

Unicon Company has been in the water / waste water and firefighting station market for over 15 years. We are dedicated to providing high-quality solutions and exceptional customer service. As we expand our team, we are looking for a talented Installation & Commissioning Engineer to join us with Avery competitive salary and benefits.<br>Key Responsibilities:Supervise the installation of all types of pumping systems and related electromechanical equipment, Manage site installation activities, ensuring compliance with project specifications, quality standards, and safety requirements, Lead testing, commissioning, start-up, and performance verification of pumping systems, Coordinate with consultants, contractors, and clients during installation and commissioning, Review shop drawings, installation procedures, and technical documentation and Prepare site reports and provide technical support to the Sales and Projects departments, Supervise subcontractors and installation teams. Required Qualifications:B. Sc. in Mechanical or Electrical Engineering. Minimum of 2-5 years of practical experience in pump installation and commissioning. Solid experience in Water and Wastewater Pumping Stations. Strong knowledge of electrical control panels, MCCs, Variable Frequency Drives (VFDs), Soft Starters, and motor control systems. Ability to troubleshoot mechanical and electrical issues during commissioning. Good knowledge of international standards and site safety procedures. Excellent communication skills and willingness to travel to project sites across Egypt.also, we are looking for firefighting sales engineer Key Responsibilities:Develop new business opportunities in the Firefighting market, Promote and sell Fire Pump Packages and Firefighting Systems, Build and maintain strong relationships with consultants, contractors, developers, and end users, prepare technical and commercial quotations, follow up on submitted offers and negotiate to secure orders, Coordinate with the technical and procurement teams to ensure customer satisfaction, Achieve assigned sales targets and provide regular sales reports. Qualifications:Bachelor’s Degree in Mechanical Engineering.1–5 years of experience in Firefighting sales. Good knowledge of NFPA Standards and Fire Pump Systems. Experience dealing with consultants, contractors, and project sales. Strong communication, presentation, and negotiation skills. Good command of English (written and spoken). Valid driving license is preferred. Also, we are looking for water utilites sales engineer Key Responsibilities:Actively engage consultants and EPC contractors on upcoming projects, penetrate new water/wastewater and industrial accounts, Support the shift toward offering Integrated Water Solutions rather than individual products, prepare technical proposals and participate in bid preparation for government and EPC projects, maintain relationships with existing clients and ensure customer satisfaction. Required Qualifications:Bachelor’s degree in Mechanical Engineering, Industrial Engineering, or a related field. Minimum 3 years’ sales experience specifically in pumps, valves, or rotating equipment. Strong technical understanding of various pump types and applications. Excellent communication skills in Arabic and English. Must own a personal car and hold a valid driver's license. Proficiency in MS Office; CRM experience is a plus.

<p>The Architectural Finishing Engineer is responsible for supervising and managing architectural finishing works on site, ensuring that all activities are executed according to approved drawings, specifications, and quality standards. The role includes reviewing project drawings, coordinating with project teams, monitoring site progress, and ensuring proper execution and handover of finishing works.</p><p><strong>Responsibilities:</strong></p><p>• Review architectural drawings, specifications, and project documents.<br>• Ensure all finishing works are executed according to approved drawings and quality standards.<br>• Prepare architectural details and coordinate with site teams for proper execution.<br>• Review and approve architectural materials and ensure compliance with project requirements.<br>• Issue architectural correspondences and follow up on site-related issues.<br>• Identify and report any architectural deviations or violations on site.<br>• Attend progress meetings and coordination meetings to resolve technical issues.<br>• Monitor site activities, supervise execution, and ensure timely completion of works.<br>• Prepare drawings and visual details using AutoCAD and other design software.<br>• Coordinate with different disciplines to ensure smooth project execution and handover.</p><p><strong>Requirements</strong></p><p>• Bachelor’s degree in Architecture Engineering.<br>• 4–5 years of experience in architectural finishing and site supervision.<br>• Previous experience in Resorts, Hotels, or Hospitality projects is preferred.<br>• Strong knowledge of finishing works, construction details, and quality standards.<br>• Proficiency in AutoCAD and Microsoft Excel.<br>• Ability to read and interpret architectural drawings and specifications.<br>• Hands-on experience in site supervision, coordination, and work handover.<br>• Strong attention to details and problem-solving skills.<br>• Ability to work with multiple disciplines and manage site activities.<br>• Excellent communication skills and ability to work effectively within a team.</p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We're looking for a driven DevOps Engineer to automate, scale, and secure our infrastructure while championing engineering best practices across the team. You'll own the full stack from cloud architecture to on-call operations and play a key role in shaping Bayzat's engineering culture. Some high-impact responsibilities you will be entrusted with:</p><ul><li>Automate tools to reduce repeating efforts of processes</li><li>Develop high quality software that is scalable and secure</li><li>Build tools and integrations that monitor and create alerts</li><li>Adapt cloud best practices</li><li>Troubleshoot errors across the entire stack - from software to hardware to cloud resources</li><li>Spread Dev-Ops culture across company</li><li>Continuously improve your technical and soft skills</li><li><br></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>3+ years experience in at least one programming language: Java, Python, Golang, or TypeScript</li><li>Strong interpersonal and communication skills in English</li><li>BS degree in Computer Science/Engineering or related technical field</li><li>Strong understanding of CS fundamentals such as data structures and algorithms</li><li>Strong debugging and troubleshooting skills</li><li>Strong experience and understanding of Git</li><li>Experience with Unix-like systems and Bash scripting</li><li>Experience with application packaging using Docker</li><li>Experience with infrastructure-as-code tools (Terraform)</li><li>Understanding of network stack basics</li><li>Solid AWS fundamentals with hands-on experience (EC2, S3, IAM, VPC, and related services)</li><li>Familiarity with Agile software development methodologies</li><li>A mindset for operational excellence</li></ul><p><strong>Nice to haves:</strong></p><ul><li>Familiarity with container orchestration technologies (Kubernetes, AWS ECS)</li><li>Familiarity with CI/CD concepts and tools (GitHub Actions)</li><li>Experience with building developer tooling and developer experience (DX)</li><li>An ability and desire to mentor and coach engineers</li><li>A deep understanding of Observability (monitoring, logging, and tracing) standard methodologies</li></ul><p></p></section>

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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.

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for a hands-on Applied Scientist / ML Engineer to support the development and improvement of AI/ML solutions, with a strong focus on Large Language Models, model accuracy, evaluation frameworks, and production-ready machine learning pipelines. The role will involve fine-tuning models, building RAG pipelines, improving prompt strategies, and collaborating with engineering teams to integrate AI capabilities into operational tools.</p><p>Key Responsibilities</p><ul><li>Fine-tune and optimize Large Language Models for domain-specific use cases.</li><li>Build evaluation frameworks to measure model quality, accuracy, and performance.</li><li>Develop and maintain RAG pipelines using operational data, documentation, and codebase references.</li><li>Design prompt engineering strategies and improve multi-step AI workflows.</li><li>Analyze model failure points, identify accuracy gaps, and recommend improvements.</li><li>Collaborate with software engineering teams to deploy model enhancements into production.</li><li>Create dashboards and reporting to track model performance and continuous improvement.</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>3+ years of hands-on experience in machine learning, deep learning, NLP, or LLM development.</li><li>Experience fine-tuning language models such as GPT, Claude, Llama, Mistral, or similar.</li><li>Strong Python skills and experience with PyTorch, TensorFlow, or Hugging Face Transformers.</li><li>Experience building end-to-end ML pipelines, including data preparation, training, evaluation, and deployment.</li><li>Knowledge of model evaluation metrics such as accuracy, F1, BLEU, ROUGE, and human evaluation methods.</li><li>Experience with RAG architectures, vector databases, and embedding models is preferred.</li><li>Familiarity with AWS ML tools such as Amazon Bedrock or SageMaker is a plus.</li><li>Ability to work independently and deliver high-quality results with minimal supervision.</li></ul><p></p></section>

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>The Senior Full Stack Engineer builds the AHOY IoT platform end to end—from device telemetry ingestion and AWS infrastructure to the real-time web dashboard.<br> We are hiring two full-stack engineers who each own complete vertical slices of the product.<br> This model ensures speed and resilience at founding stage; each engineer takes features from sensor to dashboard.<br> The trade-off is a very high bar: true backend engineering and real frontend craft in the same person.<br> As the more senior hire, you will also act as technical lead, owning the platform architecture, AWS infrastructure, and key technology decisions.<br> Key Responsibilities Backend Core Services: Build multi-tenant services from scratch: device registration/auth, alert/rule engines, notifications, and device shadow (last-known-state) services.<br> Data Pipelines: Implement the MQTT ingestion path (EMQX broker), normalize telemetry, and persist it to time-series storage and Aurora PostgreSQL (with strict row-level security).<br> APIs &amp; Real-Time: Develop versioned REST APIs (OpenAPI) and real-time delivery paths via WebSockets for high-concurrency dashboard updates.<br> Frontend App Development: Build the platform web application in Next.<br>js + TypeScript, including monitoring dashboards, onboarding wizards, and multi-tenant admin portals.<br> High-Frequency Data: Render live telemetry and time-series visualizations (line, gauge, maps) without lag, page refreshes, or memory leaks.<br> UX &amp; UI Craft: Make independent UX choices in the absence of a designer; maintain a reusable component library from Day 1 with i18n scaffolding (Arabic RTL support).<br> Architecture Infrastructure as Code: Provision and maintain AWS environments (UAE region me-central-1 for data residency) using Terraform.<br> No click-ops.<br> Scale &amp; CI/CD: Set up GitHub Actions CI/CD pipelines, operate core infrastructure (Kafka, Redis, InfluxDB), and define horizontal scaling strategies for hundreds of thousands of devices.<br> Remote Discipline: Work autonomously with proactive documentation (ADRs, runbooks) and a minimum 4-hour daily overlap with UAE working hours.<br> Must-Have Requirements Experience: 5–9 years of full-stack engineering shipping production applications (portfolio required showing deep execution on both sides).<br> Expert Frontend: React/Next.<br>js with TypeScript; proven experience handling high-frequency data streams and virtualized lists via WebSockets.<br> (Non-Negotiable) Strong Backend: Production services in Node.<br>js/TypeScript and/or Python; strong data modeling and relational performance (PostgreSQL).<br> (Non-Negotiable) IoT &amp; Messaging: Genuine literacy in MQTT protocols (topics, QoS, LWT) and device connectivity concepts.<br> (Non-Negotiable) Cloud &amp; DevOps: Hands-on AWS infrastructure deployment and GitOps-driven Terraform workflows.<br> Data Viz: Proficiency in D3.<br>js, ECharts, or similar to build custom chart types and geospatial device maps.<br> Nice to Have - Go (Golang) for high-throughput backend services.<br> - Production-scale self-hosted MQTT brokers (EMQX, HiveMQ) beyond standard AWS IoT Core.<br> - Geospatial frameworks (Mapbox GL JS, Leaflet, Deck.<br>gl). - Kafka/MSK stream processing; Keycloak for RBAC/MFA.<br> - Industrial vertical exposure (cold chain, telematics, smart buildings, predictive maintenance).<br></span> </div>

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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 Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<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. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<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.