Senior AI Research Scientist - Reinforcement Learning

Placements24; Randburg; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Fully remote work

Research incentives

Computational resources

Collaborative environment

Professional growth

Job summary

Placements24 is recruiting a Senior AI Research Scientist specializing in Reinforcement Learning for a fully remote role. You will push RL research, design novel algorithms, and apply them to real-world problems in robotics, autonomous systems, and game AI.

You'll collaborate with a world-class team, publish in top conferences, mentor junior researchers, and advance theory and practice in RL, deep learning, and simulation environments from a remote-first setup.

Qualifications

• Ph.D. or Master’s degree in CS/AI with RL focus.
• Significant RL research experience with publications or substantial contributions.
• Expertise in Python and DL frameworks such as TensorFlow, PyTorch, or JAX.
• Strong RL theory: value-based, policy-based, and model-based RL.
• Experience with simulation environments and RL libraries (OpenAI Gym, Ray RLlib).
• Excellent analytical, problem-solving, and communication skills; able to work remotely.

Responsibilities

• Conduct cutting-edge RL research and explore new algorithms.
• Design, implement, and evaluate RL agents for complex tasks.
• Develop methods for multi-agent RL, transfer learning, and safe RL.
• Collaborate with cross-functional teams to apply RL solutions.
• Publish findings in top AI conferences and journals.
• Mentor junior researchers and share knowledge.
• Analyze results and interpret model behavior.
• Stay updated on RL and related fields.
• Contribute to simulation environments and benchmarks.

Skills

Reinforcement Learning

Python

Deep Learning

TensorFlow

PyTorch

JAX

OpenAI Gym

Ray RLlib

Mathematical foundations

Research supervision

Education

PhD in Computer Science or related field

Master’s degree considered

Tools

Ray RLlib

CUDA

Git

Job description

About the Role

Our client is at the forefront of AI innovation and is actively seeking a highly accomplished Senior AI Research Scientist specializing in Reinforcement Learning (RL). This is a fully remote opportunity, allowing you to leverage your expertise from any location. You will be a key contributor to pushing the boundaries of RL research, developing novel algorithms and applying them to solve complex real-world problems. Your work will involve designing intelligent agents, optimizing decision-making processes, and contributing to advancements in areas such as robotics, autonomous systems, and game AI. You will collaborate with a world-class team of researchers and engineers, contributing to high-impact projects and shaping the future of intelligent systems. This role demands deep theoretical understanding coupled with practical implementation skills in a remote-first setting.

Key Responsibilities

• Conduct cutting-edge research in Reinforcement Learning, exploring new algorithms and theoretical frameworks.
• Design, implement, and evaluate RL agents for various complex tasks and environments.
• Develop and apply methods for multi-agent RL, transfer learning, and safe RL.
• Collaborate with cross-functional teams to integrate RL solutions into advanced applications.
• Publish research findings in top-tier AI conferences and journals.
• Mentor junior researchers and contribute to the team's technical growth and knowledge sharing.
• Analyze experimental results and provide insights into model behavior and performance.
• Stay abreast of the latest advancements in RL, deep learning, and related fields.
• Contribute to the development of simulation environments and benchmark datasets for RL research.

Requirements

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, or a related quantitative field with a strong focus on Reinforcement Learning.
• Significant research experience in Reinforcement Learning, evidenced by publications or substantial contributions.
• Expertise in Python and deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Strong theoretical understanding of RL concepts, including value-based methods, policy-based methods, and model-based RL.
• Experience with simulation environments and RL libraries (e.g., OpenAI Gym, Ray RLlib).
• Proficiency in mathematical concepts relevant to RL, such as probability, statistics, and optimization.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills for technical audiences.
• Ability to work independently and manage research projects effectively in a remote environment.

Benefits

• Highly competitive salary and research-focused incentives.
• Opportunity to lead significant research initiatives.
• Comprehensive benefits package.
• Fully remote work arrangement with flexible hours.
• Access to substantial computational resources and cutting-edge research tools.
• A stimulating and collaborative research environment.
• Significant opportunities for professional growth and impact.