Machine Learning Engineer - Benchmarking

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 advanced AI systems. The ideal candidate will possess a strong ability to bridge research and engineering, working deeply with models, data, and infrastructure within realistic ML environments to ensure system robustness and performance.

Qualifications

The successful candidate should have a minimum of three years of experience as a Machine Learning Engineer or Software Engineer with a focus on ML. Proficiency in Python is essential, especially for developing and maintaining data workflows and ML pipelines. Hands-on experience with model training, evaluation, and inference pipelines is required, along with a solid understanding of machine learning fundamentals such as supervised and unsupervised learning, evaluation metrics, and optimization techniques. Experience working with popular ML frameworks like PyTorch, TensorFlow, or JAX is highly desirable. Candidates should be comfortable navigating complex, real-world ML codebases and capable of writing clean, reusable, and maintainable production-quality code. Strong problem-solving skills, debugging capabilities, and excellent communication skills in English are also necessary to succeed in this role.

Responsibilities

Interested in remote work opportunities in Machine Learning & AI? Discover Machine Learning & AI Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.

• Collaborate with research and engineering teams to support MLE Bench–style evaluation tasks on real-world ML codebases.
• Develop, run, and refine model training, evaluation, and inference pipelines to ensure accurate benchmarking.
• Prepare datasets, features, and metrics to facilitate comprehensive ML benchmarking and validation processes.
• Debug, refactor, and optimize production-like ML systems for correctness, efficiency, and scalability.
• Assess model behavior, identify failure modes, and analyze edge cases relevant to benchmarking tasks to inform system improvements.
• Write clean, well-documented, and reproducible Python code to support ML workflows and evaluation procedures.
• Participate in code reviews to uphold high engineering standards and ensure code quality.

Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.

• Work closely with researchers and engineers to design challenging, real-world ML engineering tasks for comprehensive AI system evaluation.
  
  

Benefits

At Turing, freelancers enjoy the flexibility of working remotely from anywhere in the world, allowing for a healthy work-life balance. You will have the opportunity to engage with cutting-edge AI projects, collaborating with leading companies specializing in large language models and advanced AI systems. This role provides exposure to innovative technologies and the chance to contribute to impactful AI research and development initiatives. Additionally, Turing offers a supportive environment that values professional growth and continuous learning, making it an ideal platform for talented ML engineers seeking to expand their expertise.

Equal Opportunity

Turing is committed to fostering an inclusive and diverse work environment. We are an equal opportunity employer and welcome applications from individuals of all backgrounds, regardless of race, gender, age, religion, sexual orientation, disability, or any other characteristic protected by law. We believe that diverse perspectives and experiences drive innovation and excellence, and we are dedicated to ensuring a fair and equitable hiring process for all candidates.