Senior AI Research Scientist - Reinforcement Learning

Placements24; Stellenbosch; Híbrido; ZAR 1.200.000 - 2.100.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Highly competitive salary with bonuses

Comprehensive health insurance

Descripción de la vacante

Placements24 seeks a Senior AI Research Scientist in Stellenbosch to lead reinforcement learning research and mentor junior researchers. The role blends in-office collaboration with remote work in a hybrid setup."

You will develop novel RL algorithms, publish in top venues, and collaborate with product teams to deploy intelligent RL systems across domains. Strong publication record and deep learning proficiency are essential.

Formación

• PhD or Master's degree with a strong RL focus.
• Publications in top-tier RL venues.
• Expertise in DQN, PPO, SAC.
• Proficient in Python with TensorFlow or PyTorch.

Responsabilidades

• Conduct fundamental and applied RL research.
• Develop novel RL algorithms and frameworks for complex decision-making.
• Implement and evaluate RL models using state-of-the-art DL techniques.
• Collaborate with engineering teams to integrate RL into products.
• Publish research findings in top AI conferences and journals (e.g., NeurIPS, ICML, ICLR).
• Stay abreast of RL advancements and mentor junior researchers.

Conocimientos

Python programming

Reinforcement Learning

Research experience

Deep learning frameworks

Educación

PhD or Master’s in CS/ML/Robotics

Herramientas

TensorFlow

PyTorch

Descripción del empleo

About the Role

Our client, a globally recognized leader in AI innovation, is seeking a brilliant Senior AI Research Scientist specializing in Reinforcement Learning (RL) . This role, based in the vibrant academic hub of Stellenbosch, Western Cape , offers a hybrid work model, blending the benefits of in-office collaboration with the flexibility of remote work. You will be instrumental in pushing the frontiers of RL, tackling complex real-world problems that require advanced decision-making algorithms. Your work will directly influence the development of intelligent systems across various domains. This is an exceptional opportunity to collaborate with world-class researchers and engineers, contribute to groundbreaking research, and publish in top-tier venues. You will be expected to define research directions and mentor junior team members.

Key Responsibilities

• Conduct fundamental and applied research in reinforcement learning.
• Develop novel RL algorithms and frameworks for complex decision-making problems.
• Implement and evaluate RL models using state-of-the-art deep learning techniques.
• Collaborate with engineering teams to integrate RL solutions into products and systems.
• Publish research findings in leading AI conferences and journals (e.g., NeurIPS, ICML, ICLR).
• Stay abreast of the latest advancements in RL and related fields.
• Mentor junior researchers and contribute to the team's intellectual output.
• Design and conduct rigorous experiments to validate research hypotheses.
• Contribute to the strategic vision for RL research at Our client.

Requirements

• Ph.D. or Master's degree in Computer Science, Machine Learning, Robotics, or a related field with a strong focus on Reinforcement Learning.
• Demonstrated research contributions in RL, evidenced by publications in top-tier conferences/journals.
• Expertise in deep reinforcement learning algorithms (e.g., DQN, PPO, SAC).
• Strong programming skills in Python and experience with ML frameworks like TensorFlow or PyTorch.
• Experience with simulation environments and applied RL problems is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Effective communication and interpersonal skills, with the ability to present complex ideas clearly.
• Ability to thrive in a hybrid work environment, balancing independent work with team collaboration.

Benefits

• Highly competitive salary and performance bonuses.
• Comprehensive health insurance and retirement savings plans.
• Generous budget for professional development, conferences, and research dissemination.
• Hybrid work arrangement promoting work-life balance.
• Access to world-class computing resources.
• Intellectually stimulating work environment with opportunities for groundbreaking discoveries.
• Stock options and other long-term incentives.