Remote RL Researcher: Pioneering Algorithms & Impact

Placements24; Riverton (UT); Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Competitive salary

Research incentives

Health, dental, and vision insurance

Stock options

Remote work

Research budget

HPC access

Job summary

Placements24 is seeking a Remote Reinforcement Learning Researcher to advance cutting-edge RL research in a fully remote setting. You will explore novel RL algorithms, implement experiments, and publish results with a world-class team.

The role demands a PhD in a quantitative field, strong RL theory, and hands-on experience with Python, TensorFlow or PyTorch, and RL libraries. You will collaborate asynchronously across time zones and drive impactful research initiatives.

Qualifications

• PhD in CS/ML/AI with RL specialization.
• Strong publication record in RL conferences/journals.
• Deep RL theory knowledge: value-based, policy, model-based.
• Proficiency in Python and DL frameworks (TensorFlow, PyTorch).
• Experience with RL libraries (Stable-Baselines3, Ray RLlib).
• Strong mathematical/statistical foundation.
• Excellent analytical and communication skills.

Responsibilities

• Conduct theoretical and applied RL research.
• Design, implement, and evaluate novel RL algorithms.
• Apply RL to robotics, control, optimization problems.
• Collaborate with a remote team of researchers.
• Analyze experiments and publish findings in top venues.
• Develop RL simulation environments and benchmarks.
• Stay updated on RL and ML advancements.
• Mentor junior researchers and interns.

Skills

Reinforcement Learning

Python

Analytical thinking

Independent researcher

Education

PhD in CS/ML/AI

Tools

TensorFlow

PyTorch

Stable-Baselines3

Ray RLlib

Job description

Placements24 is seeking a Remote Reinforcement Learning Researcher to advance cutting-edge RL research in a fully remote setting. You will explore novel RL algorithms, implement experiments, and publish results with a world-class team.

The role demands a PhD in a quantitative field, strong RL theory, and hands-on experience with Python, TensorFlow or PyTorch, and RL libraries. You will collaborate asynchronously across time zones and drive impactful research initiatives.