ML Engineer – MLE Bench at Turing

ML Engineer – MLE Bench | Contractor | Remote (India, Brazil, Mexico & more)

Turing is seeking experienced Machine Learning Engineers to contribute to benchmark-driven evaluation projects focused on real-world ML systems. You'll work hands-on with production-grade codebases, training pipelines, and deployment workflows to help assess and improve the capabilities of advanced AI systems. This is a fully remote contractor role requiring at least 20 hours per week with 4 hours of PST overlap.

About Turing

Based in San Francisco, Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI. Turing accelerates frontier research with high-quality data, advanced training pipelines, and top AI researchers — and applies that expertise to help enterprises transform AI from proof of concept into measurable business impact.

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 metrics for ML benchmarking and validation.
• Debug, refactor, and improve production-like ML systems for correctness and performance.
• Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks.
• Write clean, reproducible, and well-documented Python code for ML workflows.
• Participate in code reviews to maintain high engineering standards.
• Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI evaluation.

Requirements

• 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 — supervised/unsupervised learning, evaluation metrics, optimization.
• Experience with ML frameworks such as PyTorch, TensorFlow, JAX, or similar.
• Ability to navigate and modify complex, real-world ML codebases.
• Strong problem-solving, debugging, and communication skills in English.

Engagement Details

• Type: Contractor (no medical/paid leave)
• Duration: 3 months (adjustable based on engagement)
• Hours: Minimum 20 hrs/week with at least 4 hrs/day and 4 hrs PST overlap
• Eligible Locations: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, Mexico

Evaluation Process

• Technical interview with a live coding challenge (60 minutes)