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Principal AI Engineer - Reinforcement Learning

Remote / Online - Candidates ideally in
South Africa
Listing for: Placements24
Remote/Work from Home position
Listed on 2026-10-19
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Job Description & How to Apply Below
About the Role

Our client, a global leader in applied artificial intelligence, is seeking a highly accomplished Principal AI Engineer specializing in Reinforcement Learning (RL) to join their elite, fully remote team. This is a distinguished opportunity to lead groundbreaking research and development in RL, contributing to state-of-the art applications that redefine industries. You will be instrumental in designing, implementing, and deploying complex RL algorithms and systems, pushing the boundaries of autonomous decision‑making and optimization.

The role is entirely remote, offering unparalleled flexibility and the chance to collaborate with a world‑class team from anywhere. The ideal candidate possesses a deep theoretical understanding of RL, combined with extensive practical experience in developing and deploying RL solutions in real‑world scenarios. We are looking for a thought leader who can inspire and guide junior engineers while driving innovation in a remote‑first environment.

This position is perfect for a seasoned AI professional who thrives on solving complex challenges at the cutting edge of technology, regardless of their physical location, and is seeking to contribute significantly from afar, far from
** Kimberley, Northern Cape**.

Key Responsibilities
  • Lead the research, design, and implementation of advanced Reinforcement Learning algorithms and frameworks.
  • Develop and optimise RL agents for complex decision‑making problems across various domains.
  • Architect scalable and robust RL systems for simulation and real‑world deployment.
  • Collaborate with cross‑functional teams to integrate RL solutions into existing products and services.
  • Mentor and guide junior engineers and researchers, fostering technical growth and knowledge sharing.
  • Conduct rigorous experimentation, performance analysis, and validation of RL models.
  • Stay at the forefront of RL research, publications, and industry trends, identifying novel research directions.
  • Contribute to the development of best practices and standards for RL engineering within the organization.
Requirements
  • Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related field with a strong focus on Reinforcement Learning.
  • Minimum of 7 years of hands‑on experience in AI/ML, with a significant specialization in Reinforcement Learning.
  • Proven track record of developing and deploying sophisticated RL algorithms (e.g., Q‑learning, Policy Gradients, Actor‑Critic methods).
  • Expertise in Python and ML libraries such as Tensor Flow, PyTorch, OpenAI Gym, or similar RL environments.
  • Strong understanding of deep learning principles and their application in RL.
  • Experience with large‑scale data processing and distributed computing systems.
  • Excellent problem‑solving, analytical, and critical thinking skills.
  • Exceptional communication and leadership skills, with the ability to articulate complex technical concepts.
  • Demonstrated ability to work independently and lead projects in a remote setting.
Benefits
  • As a fully remote position, we offer a highly competitive salary, performance‑based bonuses, and a comprehensive benefits package including health, dental, and vision insurance.
  • Employees are provided with a generous allowance for home office setup and professional development, including access to online courses, workshops, and conferences.
  • Our client promotes a culture of innovation, collaboration, and continuous learning, offering significant opportunities for career advancement.
  • This role offers the ultimate flexibility, allowing you to contribute your expertise from anywhere, making the specific location like
    ** Kimberley, Northern Cape
    ** irrelevant to your work.
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