Job Title: Senior Software Engineer – LLM Evaluation & Repository Validation 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. About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project. You should have experience working with well-maintained, widely-used repos with 500 stars. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality 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. What does day-to-day look like: Analyze and triage GitHub 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. Required Skills: Strong experience with at least one of the following languages: Python, JavaScript, Java, Go, Rust, C/C++, C#, or Ruby. Experience working with well-maintained, widely-used repositories with 500 stars 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. Note: Experience working with well-maintained, widely-used repositories (500 stars) is required. 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. Offer details: Commitment required: 20 hours per week with some overlap with PST Employment type: Contractor assignment (no medical/paid leave) Duration of contract: 1 month with expected start date as next week

About Us Turing is one of the world’s fastest-growing AI companies, pushing the boundaries of AI-assisted software development. Our mission is to empower the next generation of AI systems to reason about and work with real-world software repositories. You’ll be working at the intersection of software engineering, open-source ecosystems, and frontier AI. Project Overview We're building high-quality evaluation and training datasets to improve how Large Language Models (LLMs) interact with realistic software engineering tasks. A key focus of this project is curating verifiable software engineering challenges from public GitHub repository histories using a human-in-the-loop process. Why This Role Is Unique Collaborate directly with AI researchers shaping the future of AI-powered software development. Work with high-impact open-source projects and evaluate how LLMs perform on real bugs, issues, and developer tasks. Influence dataset design that will train and benchmark next-gen LLMs. What does day-to-day look like: Review and compare 3–4 model-generated code responses for each task using a structured ranking system. Evaluate code diffs for correctness, code quality, style, and efficiency. Provide clear, detailed rationales explaining the reasoning behind each ranking decision. Maintain high consistency and objectivity across evaluations. Collaborate with the team to identify edge cases and ambiguities in model behavior. Required Skills 7 years of professional software engineering experience, ideally at top-tier product companies (e.g., Stripe, Datadog, Snowflake, Dropbox, Canva, Shopify,Intuit,PayPal, Research at IBM/GE/Honewell/Scheinder etc. ). Strong fundamentals in software design, coding best practices, and debugging. Excellent ability to assess code quality, correctness, and maintainability. Proficient with code review processes and reading diffs in real-world repositories. Exceptional written communication skills to articulate evaluation rationale clearly. Prior experience with LLM-generated code or evaluation work is a plus. Bonus Points Experience in LLM research, developer agents, or AI evaluation projects. Background in building or scaling developer tools or automation systems. Engagement Details Commitment: ~20 hours/week (partial PST overlap required) Type: Contractor (no medical/paid leave) Duration: 1 month (starting next week; potential extensions based on performance and fit)

About Us Turing is one of the world’s fastest-growing AI companies, pushing the boundaries of AI-assisted software development. Our mission is to empower the next generation of AI systems to reason about and work with real-world software repositories. You’ll be working at the intersection of software engineering, open-source ecosystems, and frontier AI. Project Overview We're building high-quality evaluation and training datasets to improve how Large Language Models (LLMs) interact with realistic software engineering tasks. A key focus of this project is curating verifiable software engineering challenges from public GitHub repository histories using a human-in-the-loop process. Why This Role Is Unique Collaborate directly with AI researchers shaping the future of AI-powered software development. Work with high-impact open-source projects and evaluate how LLMs perform on real bugs, issues, and developer tasks. Influence dataset design that will train and benchmark next-gen LLMs. What does day-to-day look like: Review and compare 3–4 model-generated code responses for each task using a structured ranking system. Evaluate code diffs for correctness, code quality, style, and efficiency. Provide clear, detailed rationales explaining the reasoning behind each ranking decision. Maintain high consistency and objectivity across evaluations. Collaborate with the team to identify edge cases and ambiguities in model behavior. Required Skills 7 years of professional software engineering experience, ideally at top-tier product companies (e.g., Stripe, Datadog, Snowflake, Dropbox, Canva, Shopify,Intuit,PayPal, Research at IBM/GE/Honewell/Scheinder etc. ). Strong fundamentals in software design, coding best practices, and debugging. Excellent ability to assess code quality, correctness, and maintainability. Proficient with code review processes and reading diffs in real-world repositories. Exceptional written communication skills to articulate evaluation rationale clearly. Prior experience with LLM-generated code or evaluation work is a plus. Bonus Points Experience in LLM research, developer agents, or AI evaluation projects. Background in building or scaling developer tools or automation systems. Engagement Details Commitment: ~20 hours/week (partial PST overlap required) Type: Contractor (no medical/paid leave) Duration: 1 month (starting next week; potential extensions based on performance and fit)

About Us Turing is one of the world’s fastest-growing AI companies, pushing the boundaries of AI-assisted software development. Our mission is to empower the next generation of AI systems to reason about and work with real-world software repositories. You’ll be working at the intersection of software engineering, open-source ecosystems, and frontier AI. Project Overview We're building high-quality evaluation and training datasets to improve how Large Language Models (LLMs) interact with realistic software engineering tasks. A key focus of this project is curating verifiable software engineering challenges from public GitHub repository histories using a human-in-the-loop process. Why This Role Is Unique Collaborate directly with AI researchers shaping the future of AI-powered software development. Work with high-impact open-source projects and evaluate how LLMs perform on real bugs, issues, and developer tasks. Influence dataset design that will train and benchmark next-gen LLMs. What does day-to-day look like: Review and compare 3–4 model-generated code responses for each task using a structured ranking system. Evaluate code diffs for correctness, code quality, style, and efficiency. Provide clear, detailed rationales explaining the reasoning behind each ranking decision. Maintain high consistency and objectivity across evaluations. Collaborate with the team to identify edge cases and ambiguities in model behavior. Required Skills 7 years of professional software engineering experience, ideally at top-tier product companies (e.g., Stripe, Datadog, Snowflake, Dropbox, Canva, Shopify,Intuit,PayPal, Research at IBM/GE/Honewell/Scheinder etc. ). Strong fundamentals in software design, coding best practices, and debugging. Excellent ability to assess code quality, correctness, and maintainability. Proficient with code review processes and reading diffs in real-world repositories. Exceptional written communication skills to articulate evaluation rationale clearly. Prior experience with LLM-generated code or evaluation work is a plus. Bonus Points Experience in LLM research, developer agents, or AI evaluation projects. Background in building or scaling developer tools or automation systems. Engagement Details Commitment: ~20 hours/week (partial PST overlap required) Type: Contractor (no medical/paid leave) Duration: 1 month (starting next week; potential extensions based on performance and fit)

Job Title: Senior Software Engineer – LLM Evaluation & Repository Validation 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. About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project. You should have experience working with well-maintained, widely-used repos with 500 stars. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality 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. What does day-to-day look like: Analyze and triage GitHub 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. Required Skills: Strong experience with at least one of the following languages: Python, JavaScript, Java, Go, Rust, C/C++, C#, or Ruby. Experience working with well-maintained, widely-used repositories with 500 stars 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. Note: Experience working with well-maintained, widely-used repositories (500 stars) is required. 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. Offer details: Commitment required: 20 hours per week with some overlap with PST Employment type: Contractor assignment (no medical/paid leave) Duration of contract: 1 month with expected start date as next week

Job Description: Are you passionate about Data and Analytics (D&A) and excited about how it can completely transform the way an enterprise works? Do you have the strategic vision, technical expertise, and leadership skills to drive data-driven solutions? Do you want to work in a dynamic, fast-growing category? If so, you might be the ideal candidate for the role in the Data and Analytics function for Global Pet Nutrition (PN) at Mars. Pet Nutrition (PN) is the most vibrant category in the FMCG sector. As we work to transform this exciting category, a new program, Digital First, has been mobilized by the Mars Pet Nutrition (PN) leadership team. Digital First places pet parents at the center of all we do in Mars PN, while digitalizing a wide range of business process areas, and creating future fit capabilities to achieve ambitious targets in top line growth, earnings, and pet parent centricity. The Digital First agenda requires Digitizing at scale and requires you to demonstrate significant thought leadership, quality decision making, deep technical know-how, and an ability to navigate complex business challenges while building and leading a team of world class data and analytics leaders. With Digital First, PN is moving to a Product based model to create business facing digital capabilities. Develop and maintain robust data pipelines and storage solutions to support data analytics and machine learning initiatives. Reporting to the Director-Data engineering solution, The role operates globally in collaboration with teams engineering teams across core products. Technical Leadership - Provide strong technical leadership to data engineers and DevOps engineers across growth product teams. Act as a thought partner in the design, implementation, and evolution of scalable data platforms and assets. Champion best practices in data engineering and foster a collaborative, innovative, and high-performance culture across teams. Engineering Standards and Frameworks: Define, maintain, and evolve data engineering standards, patterns, and frameworks that product teams can adopt. Ensure consistency, quality, and reusability across solutions. Serve as a point of accountability for technical decisions and architectural direction, while empowering product teams to execute effectively. DataOps Enablement and Optimization: Drive the adoption of modern DataOps principles to streamline engineering workflows. Partner with platform teams to establish CI/CD pipelines, observability standards that improve operational efficiency, reliability, and speed across data pipelines. Data Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and formulate data priorities aimed at maximizing value through data utilization. Knowled g e / Experience Expertise in Commercial/Procurement Analytics. Experience in SAP (S/4 Hana). Experience with Spark, Databricks, or similar data processing tools. Stron g technical proficiency in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog le Bi g Query). Experience with DataOps practices and tools, includin g CI/CD for data pipelines. Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with diverse teams and stakeholders. Stron g analytical and problem-solvin g skills with a focus on driving actionable insig hts from complex data sets. LI-EN1 TBDDT Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.