AI Research Engineer - Reinforcement Learning

Placements24; Mbombela (Nelspruit); Hybrid; ZAR 1,494,000 - 2,490,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Access to computing resources

Professional development

Collaborative research environment

Job summary

Placements24 is seeking an AI Research Engineer specializing in Reinforcement Learning to design, implement, and evaluate cutting-edge RL algorithms for highly advanced projects. This fully remote role offers collaboration with researchers and engineers to push the boundaries of intelligent decision-making systems.

The ideal candidate holds a PhD or Master’s in CS/AI/ML with 3+ years of RL research, strong RL theory, and hands-on experience with Python and ML frameworks such as TensorFlow,

Qualifications

• PhD or Master’s degree in CS/AI/ML or related field.
• 3+ years of proven RL research experience.
• Strong RL concepts including Q-learning, policy gradients, and deep RL.
• Excellent communication and collaboration skills for remote work.

Responsibilities

• Conduct research and development in Reinforcement Learning, exploring new algorithms and techniques.
• Design, implement, and test RL agents for complex problems.
• Collaborate with researchers and engineers to deploy RL solutions.
• Analyze results, present findings to team and stakeholders.
• Stay current with RL advancements and related AI fields.
• Develop simulation environments for training RL agents.
• Contribute to publications, patents, and open-source projects.
• Optimize RL algorithms for performance and scalability.
• Troubleshoot and debug complex AI systems.

Skills

Reinforcement Learning theory

Python programming

Research experience

Remote collaboration

Education

PhD or Master’s in CS/AI/ML

Tools

TensorFlow

PyTorch

Ray RLlib

Job description

About the Role

Our client, a cutting-edge firm in AI & Emerging Technologies, is seeking a talented AI Research Engineer specializing in Reinforcement Learning (RL). This is a fully remote position, offering the chance to work on highly advanced projects from anywhere. You will contribute to the design, implementation, and evaluation of novel RL algorithms, pushing the boundaries of intelligent decision‑making systems. This role requires a strong theoretical foundation in machine learning and practical experience in developing and deploying RL solutions. If you are passionate about tackling complex challenges in AI research and thrive in a remote, collaborative, and innovative environment, this is an exceptional opportunity. You will be instrumental in developing next‑generation AI capabilities.

Key Responsibilities

• Conduct research and development in Reinforcement Learning, exploring new algorithms and techniques.
• Design, implement, and test RL agents for various complex problems.
• Collaborate with a team of researchers and engineers to develop and deploy RL solutions.
• Analyze experimental results, draw conclusions, and present findings to the team and stakeholders.
• Stay current with the latest advancements in RL and related AI fields.
• Develop simulation environments for training and evaluating RL agents.
• Contribute to publications, patents, and open-source projects.
• Optimize RL algorithms for performance and scalability.
• Troubleshoot and debug complex AI systems.

Requirements

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Proven research experience (3+ years) in Reinforcement Learning or a closely related area.
• Strong theoretical understanding of RL concepts (e.g., Q-learning, policy gradients, deep RL).
• Proficiency in programming languages like Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Ray RLlib).
• Experience with simulation tools and environments.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills, essential for remote work.
• Ability to work independently and manage research projects effectively.
• Publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR) are a strong plus.

Benefits

• Highly competitive compensation package.
• Fully remote work flexibility.
• Opportunity to work on groundbreaking AI research.
• Access to extensive computational resources and research data.
• Continuous learning and professional development opportunities.
• Collaborative and intellectually stimulating work environment.
• Generous vacation and wellness benefits.
• Contribution to cutting-edge AI advancements.