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About The Company 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. About The Role We are seeking experienced Machine Learning Engineers (MLE Bench) to join our team and contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves working directly with production-grade ML codebases, developing and optimizing model training and evaluation pipelines, and deploying workflows that assess and enhance the capabilities of cutting-edge AI systems. The ideal candidate will have a strong ability to bridge research and engineering, working deeply with models, data, and infrastructure within realistic ML environments to deliver impactful results. Qualifications Minimum of 3+ years of experience as a Machine Learning Engineer or Software Engineer with a focus on ML. 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, including supervised and unsupervised learning, evaluation metrics, and optimization techniques. Experience working with ML frameworks such as PyTorch, TensorFlow, JAX, or similar tools. Ability to understand, navigate, and modify complex, real-world ML codebases effectively. Proven ability to write clean, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills to troubleshoot complex issues efficiently. Excellent spoken and written communication skills in English, with the ability to collaborate effectively across teams. Responsibilities Work with real-world ML codebases to support MLE Bench-style evaluation tasks, ensuring accurate benchmarking and validation. Develop, run, and modify model training, evaluation, and inference pipelines to support ongoing research and deployment needs. Prepare datasets, features, and metrics tailored for benchmarking and validation of machine learning models. Debug, refactor, and enhance production-like ML systems to improve correctness, efficiency, and scalability. Evaluate model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks to inform system improvements. Write clean, well-documented Python code that ensures reproducibility and clarity of ML workflows. Participate in code reviews to uphold high standards of engineering quality and best practices. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for comprehensive AI system evaluation. Benefits Joining Turing as a freelance Machine Learning Engineer offers the opportunity to work remotely from anywhere in the world, providing flexibility and work-life balance. You will have the chance to contribute to pioneering AI projects with some of the leading LLM companies, gaining exposure to the latest advancements in artificial intelligence. Turing also offers a collaborative environment where your expertise will directly impact the development and deployment of cutting-edge AI systems, enhancing your professional growth and network within the AI community. Equal Opportunity Turing is committed to fostering an inclusive environment and is proud to be an equal opportunity employer. We do not discriminate based on race, ethnicity, gender, age, religion, sexual orientation, disability, or any other protected characteristic. We believe that diversity enriches our team and drives innovation. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to any protected status.