Senior AI Engineer - Reinforcement Learning

Placements24; Benoni; On-site; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Health insurance options

Relocation assistance

Professional development opportunities

Paid time off

Team events

Stock options

Job summary

Placements24 in Benoni, Gauteng, SA is seeking a Senior AI Engineer specializing in Reinforcement Learning to design and deploy RL algorithms in real-world environments. You will collaborate with researchers and engineers to tackle challenging problems and drive innovation.

The role requires 4+ years in AI/ML with RL, strong Python skills, and hands-on experience with TensorFlow or PyTorch. On-site presence in Benoni is essential to integrate with projects and teams.

Qualifications

• Master's or PhD in Computer Science, AI, Robotics or related field.
• 4+ years of AI/ML experience with reinforcement learning.
• Strong Python programming skills.
• Hands-on experience with TensorFlow or PyTorch and RL libraries.

Responsibilities

• Design, develop, and implement reinforcement learning algorithms and systems.
• Train and evaluate RL agents in simulated and real environments.
• Collaborate with researchers to explore new RL methodologies.
• Optimize RL algorithms for performance, stability, and sample efficiency.
• Integrate RL solutions into product frameworks.
• Develop robust simulation environments for training and testing RL agents.
• Analyze experimental results and provide actionable insights.
• Stay current with RL and AI research advancements.
• Mentor junior engineers and contribute to the team's growth.
• Document algorithms, code, and project findings thoroughly.

Skills

Strong coding

Python programming

Analytical thinking

Teamwork & communication

Education

Master's or PhD in CS/AI/Robotics

Tools

TensorFlow

PyTorch

Stable Baselines

Ray RLlib

Job description

About the Role

Our client is seeking a talented Senior AI Engineer specializing in Reinforcement Learning (RL) to join their innovative team. You will be at the forefront of developing intelligent systems that learn from experience to make optimal decisions in complex environments. This role involves designing, implementing, and deploying advanced RL algorithms for cutting‑edge applications. You will work closely with a team of researchers and engineers to tackle challenging problems and drive innovation. The position requires a deep understanding of RL principles, strong programming skills, and a passion for advancing AI capabilities. This role is based in **Benoni, Gauteng, ZA**, requiring on‑site presence for seamless collaboration and project integration. We are looking for a self‑motivated individual who can contribute significantly to our client’s leadership in AI. The successful candidate will be instrumental in developing next‑generation AI solutions that redefine industry standards.

Key Responsibilities

• Design, develop, and implement reinforcement learning algorithms and systems.
• Train and evaluate RL agents in simulated and real‑world environments.
• Collaborate with researchers to explore new RL methodologies and techniques.
• Optimize RL algorithms for performance, stability, and sample efficiency.
• Integrate RL solutions into existing or new product frameworks.
• Develop robust simulation environments for training and testing RL agents.
• Analyze experimental results and provide actionable insights.
• Stay current with the latest advancements in reinforcement learning and AI research.
• Mentor junior engineers and contribute to the team’s technical growth.
• Document algorithms, code, and project findings thoroughly.

Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a related field.
• 4+ years of professional experience in AI/ML, with a specialization in Reinforcement Learning.
• Strong programming skills in Python.
• Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and RL libraries (e.g., Stable Baselines, Ray RLlib).
• Deep understanding of RL concepts such as Markov Decision Processes (MDPs), Q-learning, policy gradients, and deep RL algorithms.
• Experience with simulation tools and environments.
• Excellent analytical, problem-solving, and mathematical skills.
• Strong communication and teamwork abilities.
• Ability to work effectively in a dedicated office environment.
• Experience with distributed systems is a plus.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Opportunities for professional development and attending leading AI conferences.
• Retirement savings plan with company match.
• Generous paid time off and holiday leave.
• Collaborative and innovative work environment.
• Access to high-performance computing resources.
• Relocation assistance available for qualified candidates.
• Regular team events and company social gatherings.
• Employee stock purchase plan.