Principal Machine Learning Engineer - Reinforcement Learning (Remote)

Full Description

Our client is seeking a distinguished Principal Machine Learning Engineer specializing in Reinforcement Learning (RL) to join their pioneering team in a fully remote capacity.

This is a high-impact role for an expert who will drive the research, development, and deployment of advanced RL solutions that solve complex, real-world problems.

The ideal candidate possesses a Ph.D. or equivalent researchexperience, a deep theoretical understanding of RL algorithms, and a proven track record of successfully applying RL in production environments. You will be instrumental in pushing the boundaries of what's possible with AI, contributing to groundbreaking projects that shape the future.

Responsibilities:

Lead the design, development, and implementation of state-of-the-art reinforcement learning algorithms and systems.

Conduct cutting-edge research in RL, exploring novel approaches to improve sample efficiency, stability, and generalization.

Develop and deploy RL models for complex applications such as robotics, autonomous systems, recommendation engines, and optimization problems.

Collaborate closely with research scientists and software engineers to translate theoretical advancements into practical, scalable solutions.

Mentor and guide junior machine learning engineers and researchers, fostering a culture of technical excellence and innovation.

Evaluate and benchmark the performance of RL algorithms, identifying areas for improvement and optimization.

Stay abreast of the latest research trends and advancements in machine learning and reinforcement learning.

Contribute to the overall machine learning strategy and technical roadmap of the organization.

Ensure the robustness, scalability, and maintainability of deployed RL systems.

Communicate complex technical concepts and research findings effectively to both technical and non-technical audiences.

Work collaboratively within a distributed team structure, contributing expertise from the Maiduguri, Borno, NG region to global projects.

Qualifications:

Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field, with a strong focus on Reinforcement Learning. 5+ years of hands-on experience in designing, implementing, and deploying machine learning models, with at least 3 years specifically in Reinforcement Learning.

Deep understanding of RL algorithms such as Q-learning, policy gradients, actor-critic methods, deep RL, and model-based RL.

Proficiency in programming languages like Python and experience with ML frameworks such as TensorFlow, PyTorch, or JAX. Experience with RL libraries (e.g., RLlib, Stable Baselines) and simulation environments. Strong publication record in top-tier machine learning conferences (e.g., NeurIPS, ICML, ICLR) is a significant plus.

Proven ability to tackle challenging research problems and deliver impactful results.

Excellent analytical, problem-solving, and algorithmic thinking skills. Strong communication and collaboration skills, with the ability to work effectively in a remote, team-oriented environment.