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 top AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agents. Additionally, Turing helps enterprises transform AI from proof of concept into proprietary intelligence by developing reliable systems that deliver measurable business impact and drive lasting results.

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 involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment workflows aimed at assessing and improving the capabilities of advanced AI systems. The ideal candidate will be comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic 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.
- Debug, refactor, and enhance production-like ML systems to improve correctness and performance.
- Evaluate model behavior, identify failure modes, and analyze 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 closely 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 Software Engineer with an ML focus.
- Strong proficiency in Python for machine learning and data 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 understand, navigate, 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 spoken and written English communication skills.

Preferred Qualifications and Benefits:
- Opportunity to work fully remotely, providing flexibility and work-life balance.
- Engage with cutting-edge AI projects alongside leading companies specializing in large language models (LLMs).
- Contractor assignment with a commitment of at least 4 hours per day and a minimum of 20 hours per week, including a 4-hour overlap 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 benefits or paid leave.

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 development and evaluation of advanced AI systems that have real-world impact. If you are passionate about machine learning and enjoy working in dynamic, production-like environments, this position at Turing could be an excellent fit.