Remote ML Engineer

Turing, headquartered in San Francisco, California, is a leading research accelerator for frontier AI labs 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, delivering reliable systems that create 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 experience with production-grade ML codebases, model training and evaluation pipelines, and deployment workflows. The ideal candidate will bridge research and engineering by working deeply with models, data, and infrastructure in realistic machine learning environments.

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 to enhance 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 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 ability to write readable, reusable, and maintainable production-quality code.
- Strong problem-solving and debugging skills.
- Excellent spoken and written English communication skills.

Preferred Qualifications and Benefits:
- Work remotely in a fully flexible environment.
- Opportunity to engage with cutting-edge AI projects alongside leading companies in the large language model space.
- Contractor engagement requiring a minimum commitment of 4 hours per day and 20 hours per week, with at least 4 hours overlapping with Pacific Standard Time (PST).
- Contract duration is initially 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 60-minute live coding challenge to assess their skills and suitability for the role.