Seeking experienced Machine Learning Engineers for benchmark-driven evaluation of real-world AI systems. Responsibilities include hands-on work with production ML codebases, developing training/evaluation pipelines, and deploying workflows to assess AI capabilities. Requires 3+ years of ML engineering experience with strong Python skills and ML framework knowledge.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
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 primary ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, and 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. The company's solutions ensure systems perform reliably, deliver measurable impact, and drive lasting results on the profit and loss statement. Turing’s innovative approach and commitment to excellence make it a key player in the AI industry, empowering organizations worldwide to harness the full potential of artificial intelligence technology.
About The Role
We are seeking experienced Machine Learning Engineers (MLE Bench) to join our dynamic team. In this role, you will contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. Your primary responsibilities will involve working hands-on with production-grade ML codebases, developing and refining model training and evaluation pipelines, and deploying workflows that assess and enhance the capabilities of advanced AI systems. The ideal candidate is someone who can bridge the gap between research and engineering, working deeply with models, data, and infrastructure in realistic ML environments. Your work will directly impact the evaluation and improvement of AI systems, ensuring they meet high standards of performance, robustness, and reliability.
Qualifications
- Minimum of 3+ years of experience as a Machine Learning Engineer or Software Engineer with a focus on machine learning.
- Strong proficiency in Python for developing and managing machine learning and data workflows.
- Hands-on experience with model training, evaluation, and inference pipelines in production environments.
- Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, evaluation metrics, and optimization techniques.
- Experience working with popular ML frameworks such as PyTorch, TensorFlow, JAX, or similar.
- Ability to understand, navigate, and modify complex, real-world ML codebases.
- Proven capability to write readable, reusable, and maintainable production-quality code.
- Strong problem-solving and debugging skills to troubleshoot and optimize ML systems.
- Excellent communication skills in spoken and written English, with the ability to collaborate effectively across teams.
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- Work with real-world ML codebases to support MLE Bench-style evaluation tasks, ensuring rigorous assessment of AI system capabilities.
- Build, run, and modify model training, evaluation, and inference pipelines to facilitate benchmarking and validation processes.
- Prepare datasets, features, and metrics tailored for ML benchmarking and validation activities.
- Debug, refactor, and enhance production-like ML systems to improve correctness, efficiency, and performance.
- Evaluate model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks to inform system improvements.
- Write clean, well-documented Python code for ML workflows to ensure reproducibility and maintainability.
- Participate in code reviews to uphold high standards of engineering quality and best practices.
- Collaborate closely with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.
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As a freelance contractor with Turing, you will enjoy the flexibility of working in a fully remote environment, allowing you to balance your professional and personal life effectively. You will have the opportunity to work on cutting-edge AI projects with leading companies specializing in large language models and advanced AI systems. Turing offers a dynamic and innovative work environment, providing exposure to some of the most exciting developments in artificial intelligence today. Additionally, you will have the chance to expand your professional network, enhance your skills, and contribute to impactful projects that shape the future of AI technology.
Equal Opportunity
Turing is committed to creating an inclusive environment for all employees and contractors. We are proud to be an equal opportunity employer and do not discriminate based on race, ethnicity, gender, sexual orientation, age, disability, or any other characteristic protected by law. We believe diversity drives innovation and are dedicated to fostering a respectful, equitable, and supportive workplace for everyone.
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