companyPhysical Superintelligence logo

AI Research Scientist

On-site Full-time

Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.


Unlock Your Potential

Generate Job-Optimized Resume

One Click And Our AI Optimizes Your Resume to Match The Job Description.

Is Your Resume Optimized For This Role?

Find Out If You're Highlighting The Right Skills And Fix What's Missing

Experience Level

Experience

Qualifications

Qualifications:- Proven experience in reinforcement learning.- Knowledge of distributed training systems.- Strong problem-solving skills and the ability to work collaboratively in a team-oriented environment.

About the job

AI Research Scientist

Overview

Join Physical Superintelligence, an innovative startup rooted in prestigious institutions such as Harvard, MIT, Johns Hopkins, Oxford, the Institute for Advanced Study, and the Perimeter Institute. We are at the forefront of building AI systems designed to uncover groundbreaking insights in physics on a grand scale. We are in search of talented AI researchers dedicated to developing reinforcement learning agents and training frameworks that propel scientific discovery.

Key Responsibilities

- Develop and optimize AI systems aimed at physics discovery, collaborating with physicists on verification harnesses and engineers on training infrastructure.
- Address critical AI research questions related to agent learning in physics reasoning, action space design for scientific exploration, reward structure development, and scalable training systems.
- Construct and train reinforcement learning agents leveraging cutting-edge methodologies such as PPO, SAC, MuZero, and multi-agent self-play.
- Design agent architectures tailored for physics reasoning and scientific tool utilization.
- Execute training curricula and reward structures for discovery tasks.
- Establish evaluation workflows and benchmarks to assess physics reasoning capabilities.
- Develop instrumentation to analyze agent behavior and learning dynamics.
- Collaborate closely with physicists and engineers to refine system design and architecture.

Candidate Profile

We are looking for candidates with a strong background in developing agents and training models using reinforcement learning. Proficiency in modern machine learning frameworks and experience with distributed training systems is essential, alongside a proven track record of deploying effective AI systems.

Essential Skills:

- Practical experience with contemporary reinforcement learning algorithms including PPO, SAC, MuZero, and multi-agent self-play.
- Proficient in PyTorch or JAX, with hands-on experience in distributed training using Ray, XLA, or Accelerate, and familiarity with modern pretraining workflows.

Preferred Background:

- A strong foundation in physics or mathematics that enhances intuition for physical reasoning and mathematical modeling.
- Experience applying agents in simulators, games, scientific tool use, or benchmark design employing rigorous experimental methodologies.

About Physical Superintelligence

Physical Superintelligence is a forward-thinking startup that leverages the expertise of leading academic institutions to develop advanced AI technologies aimed at transforming the field of physics and scientific exploration.

Similar jobs

Tailoring 0 resumes

We'll move completed jobs to Ready to Apply automatically.