Machine Learning Engineer (MLE Bench)

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 hands-on with production-grade ML codebases, developing and maintaining model training and evaluation pipelines, and supporting deployment workflows. The primary goal is to assess and enhance the capabilities of advanced AI systems through rigorous benchmarking and testing. The ideal candidate will possess a strong ability to bridge research and engineering, working deeply with models, data, and infrastructure in realistic ML environments. This role offers an exciting opportunity to work on cutting-edge AI projects, ensuring the robustness, reliability, and performance of AI systems in practical applications.

Responsibilities

• Work with real-world ML codebases to support MLE Bench–style evaluation tasks, ensuring accurate and reliable benchmarking processes.
• Build, run, and modify model training, evaluation, and inference pipelines to support ongoing research and deployment needs.
• Prepare datasets, features, and metrics for ML benchmarking and validation, ensuring data quality and relevance.
• Debug, refactor, and improve production-like ML systems to enhance correctness, efficiency, and scalability.
• Evaluate model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks to inform system improvements.

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• Write clean, reproducible, and well-documented Python code for ML workflows, adhering to best practices in software engineering.
• Participate in code reviews to maintain high standards of engineering quality and facilitate knowledge sharing within the team.
• Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for comprehensive AI system evaluation.
  
  

Qualifications

• Minimum 3+ years of experience as a Machine Learning Engineer or Software Engineer with a focus on ML.
• Strong 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.

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• Ability to understand, navigate, and modify complex, real-world ML codebases effectively.
• Proven track record of writing readable, reusable, and maintainable production-quality code.
• Excellent problem-solving and debugging skills, with a detail-oriented approach.
• Strong verbal and written communication skills in English, capable of collaborating effectively across teams.
  
  

Benefits

Joining Turing as a freelancer offers the flexibility to work remotely from anywhere, providing a balanced work-life environment. You will have the opportunity to work on innovative AI projects with leading LLM companies, gaining exposure to the latest advancements in artificial intelligence. Turing also offers a supportive community of talented professionals, fostering continuous learning and growth. As part of our freelance team, you will benefit from competitive compensation, flexible scheduling, and the chance to build a diverse portfolio of work in the AI domain. Additionally, Turing encourages knowledge sharing and professional development through collaborative projects and peer reviews.

Equal Opportunity

Turing is committed to fostering an inclusive environment where all individuals are valued and respected. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, or any other protected characteristic. We believe in promoting diversity in our workforce and providing equal opportunities for all talented professionals to contribute and grow within our organization.