Remote ML Engineer - Benchmarking & Production Pipelines

Turing; United States; Remote; USD 83,000 - 152,000; Part time

Benefits offered by this job

Fully remote

Work on cutting-edge AI projects

Job summary

Turing is seeking an experienced Machine Learning Engineer (MLE Bench) to contribute to benchmark-driven evaluation projects. You will work on production-grade ML codebases, train and evaluate models, and build deployment-oriented pipelines in a realistic ML environment.

The role bridges research and engineering, requiring strong Python skills, hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX), and clear communication in English.

Qualifications

• 3+ years as ML Engineer or software engineer (ML-focused).
• Strong Python for ML and data workflows.
• Hands-on experience with model training, evaluation, and inference pipelines.
• Solid understanding of ML fundamentals (supervised/unsupervised, metrics, optimization).
• Experience with ML frameworks (PyTorch, TensorFlow, JAX).
• Ability to understand, navigate, and modify complex real-world ML codebases.
• Experience writing readable, reusable production-quality code.
• Strong problem-solving and debugging skills.
• Excellent spoken and written English communication.

Responsibilities

• Work with real-world ML codebases to support MLE Bench 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 ensure high standards of engineering quality.
• Collaborate with researchers and engineers to design challenging, real-world ML tasks for AI system evaluation.

Skills

Python

ML pipelines

Model training

Evaluation metrics

Debugging

English comms

Tools

PyTorch

TensorFlow

JAX

Job description

Turing is seeking an experienced Machine Learning Engineer (MLE Bench) to contribute to benchmark-driven evaluation projects. You will work on production-grade ML codebases, train and evaluate models, and build deployment-oriented pipelines in a realistic ML environment.

The role bridges research and engineering, requiring strong Python skills, hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX), and clear communication in English.