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 accelerates cutting-edge research by providing high-quality data, advanced training pipelines, and access to top AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agents. Additionally, Turing helps enterprises transition AI from proof of concept to proprietary intelligence, delivering reliable systems that generate measurable business impact and drive sustained 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 requires hands-on experience with production-grade ML codebases, model training and evaluation pipelines, and deployment workflows. The ideal candidate will be adept at bridging research and engineering, working closely with models, data, and infrastructure in realistic machine learning 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 benchmarking and validation purposes.
- Debug, refactor, and enhance production-like ML systems to improve correctness and performance.
- Analyze model behavior, identify failure modes, and assess edge cases relevant to benchmark tasks.
- Write clean, reproducible, and well-documented Python code for machine learning 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 professional experience as a Machine Learning Engineer or Software Engineer with a focus on machine learning.
- 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 comprehend, 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 verbal and written communication skills in English.

Preferred Qualifications and Benefits:
- Fully remote work environment offering flexibility and convenience.
- Opportunity to engage with cutting-edge AI projects alongside leading companies specializing in large language models (LLMs).
- Contractor engagement requiring a commitment of at least 4 hours per day and a minimum of 20 hours per week, with a 4-hour overlap with Pacific Standard Time (PST).
- Contract duration of 3 months, adjustable based on ongoing 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 advancement of AI systems that have real-world impact. If you are passionate about machine learning and enjoy working in dynamic, production-oriented environments, Turing welcomes your application.