AI/ML Engineer - Reinforcement Learning Specialist

Placements24; Gqeberha; Hybride; ZAR 1 200 000 - 1 800 000; Plein temps

Avantages offerts par ce poste

Competitive Salary

Fully Remote

Research & Publication Opportunities

Computing Resources

Conference Allowance

Health Benefits

Home Office Setup

Résumé du poste

Placements24 is seeking a Reinforcement Learning (RL) specialist to join our fully remote team. You will design, implement, and train RL agents across robotics, game AI, and optimization, working closely with researchers from home in Port Elizabeth area or anywhere globally.

A deep theoretical foundation and practical RL experience are essential. Responsibilities include developing advanced RL algorithms, configuring simulation environments, analyzing agent behavior, and contributing to

Qualifications

• Advanced degree in CS/AI with RL focus.
• Proven hands-on experience applying RL to real-world problems.
• Strong programming skills in Python and ML libraries.

Responsabilités

• Design, implement, and train RL agents for diverse applications.
• Develop and apply advanced RL algorithms (Q-learning, Policy Gradients, Actor-Critic, Deep RL).
• Set up and manage simulation environments for training/testing RL agents.
• Analyze agent behavior, debug issues, and optimize performance for deployment.
• Collaborate with domain experts to define RL-suitable problems.
• Conduct research into novel RL techniques and publish findings.

Connaissances

Reinforcement Learning

Python

TensorFlow

PyTorch

JAX

Git

Formation

M.S./Ph.D. in Computer Science or AI (RL focused)

Outils

Stable Baselines

RLlib

OpenAI Gym

MuJoCo

Description du poste

About the Role

Our client is a cutting-edge AI research lab pushing the boundaries of autonomous systems and decision-making, and we are seeking a specialist in Reinforcement Learning (RL) to join our fully remote team. This role is for an individual with a deep theoretical understanding and practical experience in RL, eager to apply these skills to solve complex problems. You will work on developing intelligent agents and control systems that learn from interaction, contributing to breakthroughs in areas like robotics, game AI, and optimization. As a remote-first position, you will collaborate closely with a world-class team of researchers and engineers, contributing significant advancements from your home office, based in or around Port Elizabeth, Eastern Cape, ZA.

Key Responsibilities

• Design, implement, and train reinforcement learning agents for various applications.
• Develop and apply advanced RL algorithms (e.g., Q-learning, Policy Gradients, Actor-Critic methods, Deep RL).
• Set up and manage simulation environments for training and testing RL agents.
• Analyze agent behavior, debug issues, and optimize performance for real-world deployment.
• Collaborate with domain experts to define problems suitable for RL solutions.
• Conduct research into novel RL techniques and explore their potential applications.
• Stay current with the latest research papers and trends in reinforcement learning and AI.
• Contribute to internal codebases and potentially publish research findings.

Requirements

• M.Sc. or Ph.D. in Computer Science, Artificial Intelligence, or a related field with a specialization in Reinforcement Learning.
• Proven hands-on experience applying RL algorithms to solve practical problems.
• Strong programming skills in Python and experience with ML libraries like TensorFlow, PyTorch, or JAX.
• Solid understanding of deep learning fundamentals and their application in RL (Deep RL).
• Experience with RL frameworks (e.g., Stable Baselines, RLlib) and simulation tools (e.g., OpenAI Gym, MuJoCo).
• Excellent analytical and mathematical skills, with a strong grasp of probability and statistics.
• Ability to work independently, manage time effectively, and communicate technical concepts clearly in a remote setting.
• Experience with version control systems (e.g., Git).

Benefits

• Highly competitive salary and performance-based incentives.
• Fully remote work opportunity with flexible hours.
• Significant opportunities for research and publication.
• Access to powerful computing resources for model training.
• Professional development allowance for conferences and online courses.
• Collaborative and intellectually stimulating work environment.
• Comprehensive health benefits.
• Home office equipment and connectivity allowance.