Remote Machine Learning Engineer (MLE Bench)

Role Overview Turing, a globally recognised AI research accelerator headquartered in San Francisco, is seeking experienced Machine Learning Engineers to contribute to benchmark-driven evaluation initiatives focused on real-world ML systems. This is a fully remote contract opportunity ideal for professionals who thrive at the intersection of research and engineering. The role demands hands-on engagement with production-grade ML codebases, training and evaluation pipelines, and deployment-oriented workflows aimed at assessing and advancing the capabilities of cutting-edge AI systems. Key Responsibilities - 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 performance metrics for ML benchmarking and validation - Debug, refactor, and improve production-like ML systems for correctness and performance - Evaluate model behaviour, failure modes, and edge cases relevant to benchmark scenarios - Write clean, reproducible, and well-documented Python code for ML workflows - Participate in code reviews to uphold high engineering quality standards - Collaborate with researchers and engineers to design challenging real-world ML tasks for AI system evaluation Required Qualifications - Minimum 3 years of experience as a Machine Learning Engineer or ML-focused Software Engineer - Strong proficiency in Python for machine learning and data workflows - Hands-on experience with model training, evaluation, and inference pipelines - Solid understanding of ML fundamentals including supervised and unsupervised learning, evaluation metrics, and optimisation - Experience with ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent - Ability to navigate, understand, and modify complex production ML codebases - Strong problem-solving, debugging, and code documentation skills - Excellent spoken and written English communication abilities Why Join Us Turing offers the flexibility of a fully remote work environment along with the rare opportunity to contribute to frontier AI research alongside some of the world's leading LLM companies. This role is an excellent platform for ML professionals looking to apply their expertise to high-impact, cutting-edge AI evaluation projects.

- Minimum 3 years of experience as a Machine Learning Engineer or ML-focused Software Engineer - Strong proficiency in Python for machine learning and data workflows - Hands-on experience with model training, evaluation, and inference pipelines - Solid understanding of ML fundamentals including supervised and unsupervised learning - Experience with ML frameworks such as PyTorch, TensorFlow, JAX, or similar - Ability to 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 - Availability of at least 4 hours per day with a minimum of 20 hours per week and 4-hour overlap with PST

- Fully remote work environment - Opportunity to work on cutting-edge AI and frontier LLM projects - Flexible contractor engagement - Referral earning programme via turing.com/referrals