Remote Machine Learning Engineer - Reinforcement Learning

Our client is seeking a highly motivated Remote Machine Learning Engineer with a specialization in Reinforcement Learning (RL) to join their pioneering AI research and development team. This is a fully remote position, offering you the flexibility to work from your preferred location. You will be instrumental in designing, implementing, and optimizing RL algorithms for complex decision-making problems across various domains.

The ideal candidate will have a deep theoretical understanding of RL principles and practical experience in applying them to real-world challenges, such as robotics, game playing, or optimization systems. This is an exceptional opportunity to work on cutting-edge RL projects in a collaborative, remote-first environment, pushing the boundaries of AI capabilities and contributing to transformative technological advancements. You will be part of a dynamic team dedicated to solving challenging problems through innovative algorithmic approaches.

• Design, develop, and implement advanced reinforcement learning algorithms and agents.
• Train and evaluate RL models using simulations and real-world data.
• Develop environments and tools for testing and validating RL algorithms.
• Collaborate with research scientists and engineers to explore and implement novel RL techniques.
• Optimize RL algorithms for performance, scalability, and efficiency.
• Integrate RL solutions into existing systems and product pipelines.
• Stay abreast of the latest research and developments in reinforcement learning and related AI fields.
• Write high-quality, well-documented, and testable code.
• Analyze and interpret experimental results, providing insights and recommendations.
• Contribute to the team's knowledge base and best practices in RL development.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field, with a focus on Reinforcement Learning.
• Minimum of 3 years of hands‑on experience in developing and implementing RL algorithms.
• Strong theoretical understanding of RL concepts (e.g., Q‑learning, Policy Gradients, Deep RL).
• Proficiency in Python and relevant ML/RL libraries (e.g., Tensor Flow, PyTorch, Stable Baselines).
• Experience with simulation environments (e.g., OpenAI Gym, Mu Jo Co ) is highly desirable.
• Solid understanding of machine learning principles and software engineering best practices.
• Experience with data analysis and visualization tools.
• Strong problem‑solving, analytical, and critical thinking skills.
• Excellent communication and collaboration skills for effective remote teamwork.
• Familiarity with cloud computing platforms is a plus.

• Fully remote work arrangement with flexible scheduling.
• Highly competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous budget for professional development, including conferences and training.
• Opportunity to work on intellectually stimulating and impactful RL projects.
• Collaborative and supportive remote team environment.
• Generous annual leave and personal time off.
• Retirement savings plan.
• Home office setup stipend.
• Access to state-of-the- computational resources.