Basis Research
Research Scientist, Reinforcement Learning
New York Office · Junior · Full-time
Sponsorship not specifiedDetected 241 days ago
Research
About the role
- We are looking for people who are technically excellent, and who value probing concepts at their foundations.
- Our research scientists/engineers aspire to do rigorous, high-quality, robust science, but are not afraid to tinker, make mistakes, and explore radically different ideas in order to get there.
- we are looking for people who enjoy working with others on problems larger than ones they can tackle alone.
Responsibilities
- Develop and maintain open-source software
Requirements
- The second is to advance society's ability to solve intractable problems.
- This means expanding the scale, complexity, and breadth of problems that we can solve today, and even more importantly, accelerating our ability to solve problems in the future.
Compensation
- Competitive salary.
- Start date: Immediate start possible.
- Non-Discrimination Notice
- By submitting your application, you grant Basis permission to use your materials for both hiring evaluation and recruitment-related research and development purposes.
- Your information may be processed in different countries, including the US.
- You retain copyright while providing Basis a license to use these materials for the stated purposes.
Benefits
- Develop new methods and algorithms for reinforcement learning, planning, and decision-making in AI systems.
Company info
- We are in the office four days a week.
- Be prepared to attend multi-day Basis-wide in-person events.
- Basis is a collaborative effort, both internally and with our external partners; we are looking for people who enjoy working with others on problems larger than ones they can tackle alone.
- For this role, we are specifically looking for experts in Reinforcement Learning & Planning who can advance the state of the art in model-based RL, exploration strategies, optimal control, and Bayesian optimization.
- In-person Policy: We are in the office four days a week. Be prepared to attend multi-day Basis-wide in-person events.
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