Remote ML Engineer

Turing, headquartered in San Francisco, California, is a leading research accelerator for frontier AI laboratories and a trusted partner for global enterprises deploying advanced AI systems. The company supports its customers by accelerating cutting-edge research through high-quality data, advanced training pipelines, and a team of top AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agents. Additionally, Turing helps enterprises transition AI from proof of concept into proprietary intelligence, delivering reliable systems that generate measurable impact and drive lasting results on the bottom line.

We are seeking experienced Machine Learning Engineers to join our team and contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role requires hands-on involvement with production-grade ML codebases, model training and evaluation pipelines, and deployment workflows aimed at assessing and enhancing the capabilities of advanced AI systems. The ideal candidate will be adept at bridging research and engineering, working closely with models, data, and infrastructure in practical ML environments.

Key Responsibilities:
- Work directly 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 purposes.
- Debug, refactor, and optimize production-like ML systems to ensure correctness and improve performance.
- Evaluate model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks.
- Write clean, reproducible, and well-documented Python code for various 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 system evaluation.

Required Qualifications:
- Minimum of 3 years of experience as a Machine Learning Engineer or ML-focused Software Engineer.
- Strong proficiency in Python for machine learning and data processing 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 with ML frameworks such as PyTorch, TensorFlow, JAX, or similar.
- Ability to navigate, understand, and modify complex, real-world ML codebases.
- Proven track record of writing readable, reusable, and maintainable production-quality code.
- Strong problem-solving and debugging skills.
- Excellent verbal and written communication skills in English.

Preferred Qualifications and Benefits:
- Fully remote work environment offering flexibility and work-life balance.
- Opportunity to collaborate on cutting-edge AI projects with leading companies specializing in large language models (LLMs).
- Contractor engagement requiring a minimum commitment of 4 hours daily and 20 hours weekly, with at least 4 hours overlapping with Pacific Standard Time (PST).
- Initial contract duration of 3 months, with potential adjustments based on engagement.
- Note that this is a contractor role without medical or paid leave benefits.

Evaluation Process:
Candidates will undergo a technical interview featuring a live coding challenge lasting approximately 60 minutes.

This role offers a unique opportunity to work at the intersection of research and engineering, contributing to the advancement of AI systems that have real-world impact. If you are passionate about machine learning and eager to engage with complex, production-level AI workflows, Turing provides an exciting platform to grow and innovate.