Principal Machine Learning Engineer - Reinforcement Learning

Placements24; Randfontein; Hybrid; ZAR 1,800,000 - 2,400,000; Full time

Benefits offered by this job

Executive compensation

Health benefits

Relocation support

Conference budget

Pension plan

Hackathons

Job summary

Placements24 seeks a Principal Machine Learning Engineer to join a global leader in intelligent automation in Rustenburg, North West. This senior role focuses on pioneering RL advancements and building autonomous, high-performance AI systems.

You will mentor engineers, publish findings, and drive ethical AI deployment across complex industrial processes. The role offers significant research freedom and relocation support.

Qualifications

• Ph.D. or Master’s in CS/ML/AI or related field.
• 8+ years in ML with a strong RL specialization.
• Proven track record deploying RL in real-world applications.
• Proficient in Python and ML libraries (TensorFlow, PyTorch, Keras).

Responsibilities

• Lead RL research, design, and implementation.
• Develop scalable RL systems for optimization and control.
• Architect and build robust simulation environments for training.
• Collaborate with domain experts to define problems and metrics.
• Mentor junior ML engineers and researchers.
• Publish research findings in top conferences and journals.
• Contribute to IP through patents and innovations.
• Optimize RL algorithms for real-time performance.
• Ensure ethical and responsible AI development.
• Stay updated on RL and related fields.

Skills

Reinforcement Learning

Python

TensorFlow

PyTorch

Leadership

Education

PhD or Master’s in CS/ML/AI

Tools

OpenAI Gym

MuJoCo

Unity ML-Agents

TensorFlow

Job description

About the Role

Our client, a global leader in developing intelligent automation solutions, is seeking a highly accomplished Principal Machine Learning Engineer to join their elite research and development team in Rustenburg, North West. This senior position will focus on pioneering advancements in Reinforcement Learning (RL) and its applications in complex decision-making systems. You will be at the forefront of designing, building, and deploying state-of-the‑art RL agents and algorithms that drive autonomous behavior and optimize performance in critical industrial processes. This is a unique opportunity to lead significant technical initiatives, mentor talented engineers, and influence the strategic direction of AI development. We are looking for an individual with a deep theoretical understanding of RL, coupled with extensive practical experience in implementing scalable solutions. Your contributions will be vital in shaping the next generation of AI-powered automation. The role offers an intellectually stimulating environment, significant research freedom, and the chance to work on challenging, real‑world problems. Join us in Rustenburg and be part of a team that is redefining industry standards through advanced AI.

Key Responsibilities

• Lead the research, design, and implementation of novel Reinforcement Learning algorithms and models.
• Develop and deploy scalable RL systems for complex optimization and control problems.
• Architect and build robust simulation environments for training and evaluating RL agents.
• Collaborate with domain experts to define problem formulations and performance metrics for RL applications.
• Mentor and guide junior machine learning engineers and researchers.
• Stay abreast of the latest research in RL and related fields (e.g., deep learning, control theory).
• Publish research findings in top‑tier conferences and journals.
• Contribute to the company's intellectual property portfolio through patents and technical innovations.
• Optimize RL algorithms for efficiency and real‑time performance.
• Ensure the ethical and responsible development and deployment of AI systems.

Requirements

• Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• Minimum of 8 years of experience in machine learning, with a strong specialization in Reinforcement Learning.
• Proven track record of successfully developing and deploying RL solutions in real‑world applications.
• Expertise in programming languages such as Python, and proficiency with ML libraries (e.g., TensorFlow, PyTorch, Keras).
• Deep understanding of RL algorithms, including Q‑learning, Policy Gradients, Actor‑Critic methods, and model‑based RL.
• Experience with simulation tools and environments (e.g., OpenAI Gym, MuJoCo, Unity ML‑Agents).
• Strong theoretical foundation in mathematics, statistics, and linear algebra.
• Excellent problem‑solving, analytical, and critical thinking abilities.
• Strong leadership and communication skills, with the ability to mentor and guide teams.
• Experience with large‑scale data processing and distributed computing is a plus.

Benefits

• Executive‑level compensation package, including significant bonuses and potential equity.
• Comprehensive health, dental, and vision insurance for employees and dependents.
• Generous vacation policy and paid time off.
• Significant budget for professional development, conferences, and advanced training.
• Access to world‑class computing infrastructure and cutting‑edge research tools.
• Opportunity to work on highly impactful and challenging projects.
• Relocation assistance provided for successful candidates.
• Contribution to a leading pension fund.
• Regular innovation challenges and hackathons.
• A culture that values intellectual curiosity and scientific exploration.