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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.

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks. You'll create challenging tasks and evaluation criteria within realistic simulated environments:</p><p>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history</p><p>Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent</p><p>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient</p><p>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust</p><p>What this is NOT:</p><ul><li>Not data labeling</li><li>Not prompt engineering</li><li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate</li></ul><p>What we look for:</p><ul><li>8+ years in software development</li><li>Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis</li><li>Experience writing tests (functional, integration)</li><li>English proficiency - B2+</li></ul><p>Why this is hard:</p><ul><li>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.</li><li>Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.</li></ul><p><br></p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p><br></p><p></p></section>

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.

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><br></p><ul> </ul> <p> </p> <p> <strong>Your day-to-day could include: </strong> </p> <ul> <li>Prepare, deploy, and operate advanced downhole tools to meet specific wellsite objectives </li> <li>Utilize cutting-edge simulation software to design and optimize wellsite solutions tailored to client needs </li> <li>Analyse performance data and recommend improvements </li> <li>Manage equipment logistics and ensure seamless setup and operation at the rig site </li> <li>Create detailed post-job reports and share actionable insights with clients and internal teams </li> <li>Champion a culture of continuous improvement with a strong focus on safety, quality, and performance </li> <li>Deliver front-line engineering support to our customers throughout operations, resolving issues independently </li> </ul> <p> </p> <p> <strong>What We re Looking For</strong> </p> <ul> <li>Graduated with bachelor s degree in engineering (all fields) within the last 24 months </li> <li>No more than 1 year of experience </li> <li>English language fluent proficiency (written and spoken) </li> <li>Strong communication and interpersonal skills </li> <li>Ability to analyse complex problems, apply critical thinking, and make informed decisions </li> <li>A passion for hands-on work and learning in dynamic environments (onshore and offshore) </li> </ul> <p> </p> <p> <strong>What to Expect</strong> </p> <p>This role is physically and mentally demanding. You ll work 12-hour shifts (day or night), often in tough weather conditions. You may be away from home for extended periods, including weekends and holidays. But if you re up for the challenge, the rewards are big. </p> <p>You ll join one of our specialized product lines, such as: </p> <ul> <li>Completions </li> <li>Drilling Services </li> <li>Wireline Services </li> <li>Artificial Lift </li> <li>Well Services </li> <li>Managed Pressure Drilling and many more </li> </ul> <p> </p> <p><br></p> <p> </p></div></section>

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: 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: 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: 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.