Senior AI Researcher (Reinforcement Learning)

Placements24; Noord-Kaap; Hybrid; ZAR 1.000.000 - 2.000.000; Vollzeit

Benefits dieser Stelle

Competitive salary

Comprehensive health benefits

Generous paid time off

State-of-the-art research facilities

Hybrid work flexibility

Professional development opportunities

Zusammenfassung

Placements24 in Kimberley invites a Senior AI Researcher specializing in Reinforcement Learning to join our hybrid research hub. You will lead cutting-edge RL projects, craft novel algorithms, and run rigorous experiments that advance autonomous learning systems.

Ideal candidates hold a PhD in a quantitative field and have a track record of high-impact RL publications. You will mentor juniors and collaborate with engineers to deploy scalable RL solutions across products.

Qualifikationen

• PhD in Computer Science, AI, ML or related quantitative field with a strong RL focus.
• Proven track record in RL research, evidenced by publications in top venues.
• Strong theoretical RL foundations: value-based methods, policy gradients, exploration.

Aufgaben

• Conduct advanced RL research and develop novel RL algorithms.
• Design and run experiments to evaluate RL agents in simulations and real data.
• Collaborate with engineering teams to integrate RL into products.
• Publish results in leading AI conferences and journals.
• Mentor junior researchers and share knowledge across the team.

Kenntnisse

Reinforcement Learning

Python

Deep Learning

Experiment Design

Distributed Training

Ausbildung

PhD in Computer Science / AI / ML

Tools

TensorFlow

PyTorch

Jobbeschreibung

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 contribute 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.