Remote Reinforcement Learning Researcher

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

About the Role

Our client, a leader in cutting-edge research within the **AI & Emerging Technologies** sector, is actively seeking a highly motivated and innovative Remote Reinforcement Learning Researcher. This fully remote position allows you to conduct groundbreaking research and development in reinforcement learning (RL) from anywhere in the world. You will be at the forefront of developing novel RL algorithms and applying them to solve complex, real-world problems across various domains. The role demands a deep theoretical understanding of RL, coupled with practical experience in implementing and experimenting with RL agents. You will collaborate with a globally distributed team of world-class scientists and engineers, utilizing advanced computational resources. This remote-first role champions asynchronous communication and collaborative platforms to ensure seamless teamwork and knowledge sharing. If you are passionate about advancing the field of reinforcement learning and thrive in an independent, research-focused remote environment, this opportunity is ideal for you. While the role is remote, its conceptual foundation aligns with our strategic development originating from Upington, Northern Cape .

Key Responsibilities

• Conduct theoretical and applied research in reinforcement learning algorithms.
• Design, implement, and evaluate novel RL algorithms and approaches.
• Apply RL techniques to solve challenging problems in areas such as robotics, control systems, and optimization.
• Collaborate effectively with a remote team of researchers and engineers.
• Analyze experimental results, draw insights, and publish findings in top-tier conferences and journals.
• Develop simulation environments and benchmarks for RL research.
• Stay abreast of the latest advancements in RL, machine learning, and related fields.
• Contribute to the strategic direction of RL research within the organization.
• Mentor junior researchers and interns.

Requirements

• Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field with a specialization in Reinforcement Learning.
• Proven track record of research in reinforcement learning, demonstrated through publications in leading conferences/journals.
• Deep understanding of RL theory, including value-based methods, policy gradient methods, and model-based RL.
• Expertise in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with RL libraries and frameworks (e.g., Stable-Baselines3, Ray RLlib).
• Strong mathematical and statistical foundation.
• Excellent analytical, problem-solving, and critical thinking skills.
• Demonstrated ability to work independently and conduct high-quality research in a remote setting.
• Strong written and verbal communication skills for remote collaboration.

Benefits

• Highly competitive salary and research-based incentives.
• Comprehensive health, dental, and vision insurance.
• Generous stock options and performance bonuses.
• Fully remote work arrangement with significant flexibility.
• Substantial budget for research, conferences, and publication fees.
• Opportunity to work on groundbreaking **AI & Emerging Technologies** research.
• Access to high-performance computing resources.
• Supportive and intellectually stimulating remote research community.