Remote ML Engineer

Turing, headquartered in San Francisco, California, is a global leader in accelerating frontier AI research and a trusted partner for enterprises deploying advanced AI systems. The company supports its customers by providing high-quality data, sophisticated training pipelines, and access to top AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agent-based systems. Additionally, Turing helps enterprises transition AI from experimental stages into reliable, proprietary intelligence that delivers measurable business impact and drives sustainable results.

We are seeking experienced Machine Learning Engineers to join our team and contribute to benchmark-driven evaluation projects centered 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 enhancing advanced AI capabilities. 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 pipelines for model training, evaluation, and inference.
- Prepare datasets, features, and metrics to facilitate ML benchmarking and validation.
- Debug, refactor, and optimize production-like ML systems to ensure correctness and performance.
- Analyze model behavior, identify failure modes, and address edge cases relevant to benchmark objectives.
- 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 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 working 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:
- Fully remote work environment offering flexibility.
- 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 per day and 20 hours per week, with at least 4 hours overlapping with Pacific Standard Time (PST).
- Initial contract duration of 3 months, with potential adjustments based on engagement.
- This is a contractor role without medical benefits or paid leave.

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

This role offers a unique opportunity to work at the intersection of AI research and engineering, contributing to impactful projects that push the boundaries of machine learning technology.