Applied Researcher in Reinforcement Learning
virtual vocationsDenver (CO)
Applied Researcher in Reinforcement Learning
Posted today
virtual vocationsDenver (CO)
SENIORITY
Senior
About the role
Focusing on reinforcement learning for agents that reason over long horizons, the full-time Applied Researcher in Reinforcement Learning will develop scalable systems and methods while collaborating with application teams and open-source users, with the flexibility to work remotely or from major cities like San Francisco, London, or New York.
Key responsibilities:
Develop RL and post-training methods for tool-using, multi-agent, memory-augmented, and long-horizon systems
Create reusable environments, harnesses, rewards, and evaluations for reinforcement learning applications
Conduct experiments connecting algorithm choices to training and inference behavior, while extending existing research initiatives
Required qualifications:
Hands-on experience with RL training, scalable ML systems, and agent environments
Proven ability to build and debug model-training and evaluation loops
Strong experimental judgment and the capability to adapt based on evidence
Proficiency in Python and experience creating artifacts for research and engineering use
Comfort in managing ambiguous problems and maintaining communication with partners and teammates
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
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Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.