Senior AI Researcher (Reinforcement Learning)

Placements24; Kimberley (AR); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Highly competitive salary

Comprehensive health benefits

Generous paid time off

State-of-the-art research facilities

Job summary

Placements24 is seeking a Senior AI Researcher specializing in Reinforcement Learning to join our Kimberley team in a hybrid role. You will lead theoretical and applied RL research, design and implement cutting-edge algorithms, and mentor junior researchers while collaborating with engineers to integrate RL into products.

The role emphasizes developing scalable RL training infrastructure, publishing in top venues, and staying at the forefront of AI advancements, with in-person collaboration in

Qualifications

• PhD in a relevant field with strong RL focus.
• Significant RL research contributions with publications.
• Proficiency in Python and DL frameworks.

Responsibilities

• Conduct advanced RL research and develop novel algorithms.
• Implement RL methods and validate in simulations and real data.
• Design experiments to evaluate RL agents and scalable training.
• Publish findings in top AI venues and contribute to team knowledge.

Skills

Reinforcement Learning

Deep Learning

Python

Experimentation

Distributed Training

Education

PhD in Computer Science/AI/ML

Tools

TensorFlow

PyTorch

Job description

About the Role

Our client is seeking a highly skilled and innovative Senior AI Researcher specializing in Reinforcement Learning (RL) to join their team in Kimberley . This hybrid role offers a unique opportunity to conduct cutting-edge research and development in RL, contributing to the creation of intelligent systems that learn and adapt autonomously. You will work on challenging problems, design novel algorithms, and implement advanced RL techniques. The ideal candidate possesses a strong theoretical foundation in RL, coupled with practical experience in applying it to complex domains. You will collaborate with a team of world-class researchers and engineers, pushing the boundaries of artificial intelligence. The hybrid work model provides flexibility, allowing for focused remote work alongside valuable in-person collaboration in our Kimberley research hub.

Key Responsibilities

• Conduct advanced research in Reinforcement Learning theory and applications.
• Develop and implement novel RL algorithms and frameworks.
• Design and execute experiments to evaluate the performance of RL agents.
• Analyze complex simulation environments and real-world data.
• Collaborate with engineering teams to integrate RL solutions into products.
• Publish research findings in top-tier AI conferences and journals.
• Stay abreast of the latest research and advancements in RL and related fields.
• Mentor junior researchers and contributions to team knowledge sharing.
• Contribute to the development of efficient and scalable RL training infrastructure.
• Present research findings to internal teams and external stakeholders.

Requirements

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field, with a strong focus on Reinforcement Learning.
• Demonstrated track record of significant research contributions in RL, evidenced by publications in leading venues.
• Deep theoretical understanding of RL concepts, including value-based methods, policy gradient methods, and exploration strategies.
• Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience implementing RL algorithms in various environments (e.g., OpenAI Gym, custom simulators).
• Strong analytical and mathematical skills.
• Excellent problem-solving abilities.
• Effective communication and collaboration skills for a hybrid work setting.
• Ability to work both independently and as part of a research team.
• Experience with distributed training and large-scale experiments is a plus.

Benefits

• Highly competitive salary and performance-based incentives.
• Comprehensive health, dental, and vision benefits.
• Generous paid time off and professional development opportunities.
• Access to state-of-the-art research facilities and computing resources in Kimberley .
• A stimulating and collaborative research environment.
• Hybrid work flexibility.
• Opportunity to work on groundbreaking RL research.