Machine Learning Engineer (MLE Bench)

About The Company

Turing is a leading research accelerator based in San Francisco, California, dedicated to advancing frontier AI research and supporting global enterprises in deploying sophisticated AI systems. As a trusted partner to some of the world's most innovative organizations, Turing specializes in accelerating research through high-quality data, cutting-edge training pipelines, and top-tier AI researchers with expertise in coding, reasoning, STEM, multilinguality, multimodality, and agent systems. The company's mission is to transform AI from proof-of-concept prototypes into reliable, proprietary intelligence solutions that deliver measurable business impact and drive sustainable growth. Turing's commitment to innovation and excellence positions it at the forefront of AI development, fostering a collaborative environment where talent and technology intersect to push the boundaries of what AI can achieve.

About The Role

We are seeking experienced Machine Learning Engineers (MLE Bench) to join our dynamic team. This role focuses on benchmark-driven evaluation projects centered around real-world machine learning systems. As an MLE Bench, you will work hands-on with production-grade ML codebases, developing and refining model training, evaluation, and deployment pipelines to assess and enhance the capabilities of advanced AI models. Your contributions will directly influence the development of robust AI systems by identifying performance bottlenecks, failure modes, and edge cases, ensuring models operate reliably in diverse scenarios.

The ideal candidate will possess a strong ability to bridge research and engineering, working deeply with models, data, and infrastructure within realistic ML environments. You will collaborate closely with research teams and engineering colleagues to design challenging evaluation tasks, improve system performance, and ensure the reproducibility and maintainability of ML workflows. This role offers an exciting opportunity to be at the forefront of AI evaluation, working on cutting-edge projects that shape the future of artificial intelligence.

Qualifications

• Minimum of 3+ years of professional experience as a Machine Learning Engineer or Software Engineer with a focus on ML systems.
• Proficiency in Python, with extensive experience in developing, debugging, and optimizing ML workflows.
• Hands-on experience with model training, evaluation, and inference pipelines in production environments.
• Strong understanding of core machine learning concepts, including supervised and unsupervised learning, evaluation metrics, and optimization techniques.
• Experience working with popular ML frameworks such as PyTorch, TensorFlow, JAX, or similar tools.
• Ability to navigate, understand, and modify complex, real-world ML codebases effectively.
• Proven track record of writing clean, reusable, and maintainable production-quality code.

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• Excellent problem-solving skills with a keen eye for debugging and performance optimization.
• Strong communication skills, both written and spoken, with the ability to articulate technical concepts clearly in English.
  
  

Responsibilities

• Work with real-world ML codebases to support evaluation tasks aligned with MLE Bench standards.
• Build, run, and refine model training, evaluation, and inference pipelines to ensure robustness and efficiency.
• Prepare datasets, features, and metrics tailored for benchmarking and validation purposes.
• Debug, refactor, and enhance production-like ML systems to improve correctness, performance, and scalability.
• Assess model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks.
• Develop clean, well-documented, and reproducible Python code for ML workflows and evaluation scripts.
• Participate in code reviews to uphold high engineering standards and foster knowledge sharing within the team.

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• Collaborate with researchers and engineers to design and implement challenging evaluation scenarios for AI systems.
  
  

Benefits

• Opportunity to work remotely from anywhere, providing flexibility and work-life balance.
• Engage in cutting-edge AI projects with leading LLM companies and innovative research teams.
• Gain exposure to advanced AI evaluation methodologies and real-world deployment challenges.
• Collaborate with a global network of top-tier AI professionals and researchers.
• Enhance your skills and experience in a rapidly evolving technological landscape.
  
  

Equal Opportunity

Turing is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and applicants. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, disability, or any other protected characteristic. We believe that diverse teams foster innovation and drive better results, and we are dedicated to providing equal employment opportunities to all individuals.