Senior RL Engineer – Hybrid Role with Growth

Placements24; Southampton; On-site; GBP 54,000 - 81,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Performance bonuses

Professional development

Job summary

Unknown AI Firm in Randburg, Gauteng seeks a Senior AI/ML Engineer specializing in reinforcement learning to design and deploy advanced RL solutions. You will build training simulations, evaluate agents, and collaborate with product teams to integrate AI capabilities across services.

The role emphasizes deep theoretical knowledge with practical deployment experience, mentoring, and ongoing research contributions in a dynamic, innovative setting.

Qualifications

• Master's or PhD in CS/AI/Robotics or related field.
• 5+ years of RL algorithm development experience.
• Strong Python and deep learning framework skills (TensorFlow, PyTorch).
• Experience with RL libraries such as Ray RLlib and Stable Baselines.
• Familiarity with simulation environments and parallel computing.

Responsibilities

• Design, implement, and optimize RL algorithms.
• Develop simulation environments to train RL agents.
• Collaborate with cross-functional teams to deploy RL solutions.
• Explore deep RL, multi-agent RL, and model-based RL topics.
• Ensure scalability, efficiency, and robustness of RL systems.
• Stay current with AI research and industry trends.
• Mentor junior engineers and share knowledge.
• Analyze experiments and provide actionable insights.
• Document research and project findings.

Skills

Reinforcement Learning

Python

Deep Learning

Ray RLlib

Mentoring

Education

Master's/PhD in CS/AI/Robotics

Tools

TensorFlow

PyTorch

Stable Baselines

Ray RLlib

Job description

Unknown AI Firm in Randburg, Gauteng seeks a Senior AI/ML Engineer specializing in reinforcement learning to design and deploy advanced RL solutions. You will build training simulations, evaluate agents, and collaborate with product teams to integrate AI capabilities across services.

The role emphasizes deep theoretical knowledge with practical deployment experience, mentoring, and ongoing research contributions in a dynamic, innovative setting.