TensorOps is looking for a part-time Machine Learning Engineer to join our mission of building the talent engine that helps leading labs and research organizations advance AI. In this remote, asynchronous role, you will focus on benchmarking and improving model performance and training speed across real ML workloads.
What You'll Do
- Draft detailed natural-language plans and code implementations for machine learning tasks
- Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments
- Identify failure modes and apply golden patches to LLM-generated trajectories for machine learning tasks
What We're Looking For
- 0–2 years of experience as a Machine Learning Engineer OR a PhD in Computer Science with relevant Machine Learning coursework
- Expertise in Python and ML libraries like XGBoost, TensorFlow, and scikit-learn
- Hands-on experience with data preparation and model training
- Applicant MUST be based in the United States
Nice to Have
- Experience as a contributor to ML benchmarks
Technical Stack
- Python
- XGBoost
- TensorFlow
- scikit-learn
Work Mode
This is a remote, part-time, asynchronous position open to candidates based in the United States.
