AI System Evaluation Engineer (Data Science)

Role Overview: You will be joining as an experienced Software Engineer in the SWE Bench team, focusing on Data Engineer and Data Science projects that involve benchmark-driven evaluation tasks using real-world data engineering and data science workflows. Your responsibilities will include working with production-like datasets, designing, building, and validating data pipelines, performing data processing, analysis, and model-related workflows, writing and modifying Python code, evaluating data quality, and creating clean, well-documented data workflows suitable for benchmarking. Additionally, you will collaborate with researchers and engineers to design challenging tasks for AI systems. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines for benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science use cases. - Write, run, and modify Python code to process data and support experiments locally. - Evaluate data quality, transformations, and outputs for correctness and reproducibility. - Create clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to ensure high standards of code quality and maintainability. - Collaborate with researchers and engineers to design challenging real-world data engineering and data science tasks for AI systems. Qualifications Required: - Minimum 3+ years of experience as a Data Engineer, Data Scientist, or Software Engineer with a data focus. - Strong proficiency in Python for data engineering and data science workflows. - Demonstrable experience with data processing, analysis, and model-related workflows. - Solid understanding of machine learning and data science fundamentals. - Experience working with structured and unstructured data. - Ability to understand, navigate, and modify complex, real-world codebases. - Experience in writing readable, reusable, maintainable, and well-documented code. - Strong problem-solving skills, including experience with algorithmic or data-intensive problems. - Excellent spoken and written English communication skills. In addition to the above details, Turing is based in San Francisco, California, and is known as the world's leading research accelerator for frontier AI labs. They are a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers by accelerating frontier research and helping enterprises transform AI into proprietary intelligence with systems that deliver measurable impact and drive lasting results on the P&L. If you are looking to freelance with Turing, you will have the opportunity to work in a fully remote environment and work on cutting-edge AI projects with leading LLM companies. Please note the commitments required for this role: At least 4 hours per day and a minimum of 20 hours per week with an overlap of 4 hours with PST. The engagement type is a Contractor assignment with no medical/paid leave, and the duration of the contract is 3 months, adjustable based on engagement. After applying, you will receive an email with a login link to access the portal and complete your profile. If you know any talented individuals, you can refer them and earn money from your network. Role Overview: You will be joining as an experienced Software Engineer in the SWE Bench team, focusing on Data Engineer and Data Science projects that involve benchmark-driven evaluation tasks using real-world data engineering and data science workflows. Your responsibilities will include working with production-like datasets, designing, building, and validating data pipelines, performing data processing, analysis, and model-related workflows, writing and modifying Python code, evaluating data quality, and creating clean, well-documented data workflows suitable for benchmarking. Additionally, you will collaborate with researchers and engineers to design challenging tasks for AI systems. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines for benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science use cases. - Write, run, and modify Python code to process data and support experiments locally. - Evaluate data quality, transformations, and outputs for correctness and reproducibility. - Create clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to ensure high standards of code quality and maintainability. - Collaborate with researchers and engineers to design challenging real-world data engineering and data science tasks for AI systems. Qualifications Required: - Minimum 3+ years of experience as a Data Engineer, Data Scientist, or Software Engineer with a data