Machine Learning Researcher

Research Engineer – Agentic AI & Automation

Building agentic systems that move beyond demos, toward autonomous research collaborators, decision-making systems, and production-grade AI operators.

We are looking for a Research Engineer to partner directly with research scientists to turn frontier ideas into scalable, reliable systems.

This is not prompt engineering. This is not wrapper-building. This is systems-level autonomy engineering.

What You’ll Do Architect and implement multi-agent systems with memory, planning, and tool use Design robust orchestration frameworks for long-horizon reasoning Translate novel research (RL, planning, tool-augmented LLMs) into working infrastructure Build evaluation harnesses for agent reliability, failure detection, and safety Develop scalable experiment pipelines for rapid iteration Improve observability, debugging, and introspection of autonomous systems

Work at the intersection of: Reinforcement learning LLM reasoning & tool use o Retrieval systems Real-world automation You will sit between research and production and raise the bar for both.

What We’re Looking For Background

Experience at a frontier AI lab or high-performance AI company Strong systems engineering mindset Deep comfort working with ambiguity and open research problems Technical Depth • Expert-level Python Strong PyTorch experience Experience building distributed systems Experience with agent frameworks, RL systems, or large-scale LLM evaluation Familiarity with planning algorithms, memory architectures, or tool-calling systems Experience running large-scale experiments on GPU clusters Bonus Experience with autonomous coding agents Experience optimizing LLM inference pipelines Published research in ML, RL, or systems Experience working closely with research scientists