onsite
AI/ML Engineer - Reuben Cooley Inc
ML Engineer
Design and implement decision‑making frameworks for autonomous AI agents, create evaluation metrics, and apply LLM tuning techniques such as fine‑tuning, prompt engineering, and RLHF using Python and deep‑learning libraries.
About the role
Key Responsibilities
- Design, develop, and integrate behavioral logic and decision‑making pipelines for autonomous AI agents.
- Build and maintain robust evaluation metrics, testing suites, and benchmarking tools to measure agent performance.
- Analyze large language model (LLM) outputs, identify failure modes, and propose improvements for agentic tasks.
- Apply LLM tuning methods including fine‑tuning, prompt engineering, and Reinforcement Learning from Human Feedback (RLHF).
- Collaborate with cross‑functional teams to deploy models in production environments and ensure scalability.
Requirements
- Strong proficiency in Python and experience with deep‑learning frameworks such as PyTorch or TensorFlow.
- Hands‑on experience with large language models, prompt engineering, and RLHF techniques.
- Solid understanding of machine‑learning concepts, evaluation methodologies, and model optimization.
- Ability to design reproducible experiments, analyze results, and iterate quickly.
- Excellent problem‑solving skills and ability to work independently in a fast‑paced research environment.
Skills
pythonpytorchtensorflowmachine learning