Remote Machine Learning Engineer (Benchmark Evaluation)

About the role

Turing is seeking an experienced Machine Learning Engineer to work on benchmark‑driven evaluation projects for advanced AI systems. This fully remote contractor role focuses on production‑grade ML codebases, model training, evaluation pipelines, and deployment‑oriented workflows.

Key responsibilities

• Develop, run, and modify model training, evaluation, and inference pipelines for real‑world ML benchmarks.
• Prepare datasets, feature sets, and metrics to support ML validation and benchmarking.
• Debug, refactor, and improve production‑like ML systems for correctness and performance.
• Assess 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 and collaborate with researchers and engineers to design challenging evaluation tasks.

Required profile

• Minimum 3 + years of experience as a Machine Learning Engineer or Software Engineer with an ML focus.
• Strong proficiency in Python for data and ML workflows.
• Hands‑on experience building and maintaining model training, evaluation, and inference pipelines.
• Excellent spoken and written English communication skills.

Required skills

• Python
• PyTorch
• TensorFlow
• JAX
• Machine learning fundamentals (supervised/unsupervised learning, metrics, optimization)
• Experience with complex, production‑grade ML codebases

What we offer

• Fully remote work environment.
• Opportunity to contribute to cutting‑edge AI projects with leading LLM companies.
• Flexible contractor schedule (minimum 4 hours/day, 20 hours/week with 4 hours overlap PST).