Remote Reinforcement Learning Researcher

Placements24; Upington; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Stock options

Remote work

Conference budget

AI research opportunities

HPC access

Remote research community

Job summary

Placements24 is seeking a remote Reinforcement Learning Researcher to lead theoretical and applied RL research. You will design and implement novel RL algorithms, publish results, and mentor juniors while collaborating with a global team.

The role offers a fully remote setup and strong support for research activities. Applicants should hold a PhD with RL specialization, publish in top venues, and demonstrate expertise in Python, TensorFlow/PyTorch, and RL libraries.

Qualifications

• PhD in CS/ML/AI with RL specialization.
• Publications in leading RL conferences/journals.
• Strong RL theory: value-based, policy gradient, model-based.
• Proficiency in Python and DL frameworks (TensorFlow, PyTorch).
• Experience with RL libraries (Stable-Baselines3, Ray RLlib).
• Strong math and statistics foundation.
• Excellent analytical and problem-solving skills.
• Ability to work independently in a remote setting.
• Strong written and verbal communication for remote collaboration.

Responsibilities

• Conduct theoretical and applied RL research.
• Design, implement, and evaluate novel RL algorithms.
• Apply RL to robotics, control, and optimization.
• Collaborate effectively with a remote team of researchers.
• Analyze experiments, publish findings in top-tier venues.
• Develop simulation environments and benchmarks for RL research.
• Stay abreast of RL, ML advancements.
• Contribute to strategic direction of RL research.
• Mentor junior researchers and interns.

Skills

Reinforcement Learning theory

Python programming

TensorFlow

PyTorch

RL libraries

Research publications

Education

PhD in Computer Science / ML / AI with RL specialization

Tools

Stable-Baselines3

Ray RLlib

TensorFlow

PyTorch

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.