Full Stack Reinforcement Learning (RL) Engineer Specialist - Freelance Project

<p><strong>What You’ll Do</strong><strong><br></strong>Support projects by designing and implementing reinforcement learning systems that bridge research and deployment. Work across the stack to contribute to both backend services and frontend interfaces that enable RL-driven applications.</p> <ul> <li><strong>Develop RL Models and Pipelines:</strong> Design, train, and evaluate reinforcement learning models tailored to dynamic environments and optimization problems.</li> <li><strong>Application Integration:</strong> Collaborate with engineers and data scientists to integrate RL models into production systems and interfaces, ensuring usability and performance.</li> <li><strong>Full Stack Contribution:</strong> Contribute to backend services, APIs, and React-based frontends supporting RL experiments and applications.</li> <li><strong>Data Exploration and Experimentation:</strong> Work with large-scale datasets and simulation environments to inform model development and evaluation.</li> </ul> <p><strong>What We Need</strong></p> <p><strong>Professional Experience:</strong></p> <ul> <li>3+ years of experience building and deploying ML systems, with at least 1+ year focused on reinforcement learning.</li> <li>Background contributing to both backend and frontend components of production-grade systems.</li> <li>Experience engaging with stakeholders or project teams to refine requirements and translate into technical deliverables.</li> </ul> <p><strong>Technical Expertise:</strong></p> <ul> <li>Strong programming skills in Python and JavaScript (or similar), with proficiency in frameworks such as PyTorch, TensorFlow, or JAX for RL.</li> <li>Familiarity with RL libraries and environments (e.g., OpenAI Gym, RLlib, Stable Baselines, custom simulators).</li> <li>Experience with backend frameworks (FastAPI, Flask, or similar) and frontend frameworks (React, Vue, or similar).</li> <li>Comfort with containerization and cloud environments (GCP, AWS, or similar).</li> <li>Understanding of distributed training, scaling RL systems, and experiment tracking.</li> <li>Ability to produce clean, modular, and testable code in collaborative environments.</li> </ul> <p><strong>Important:</strong></p> <p>We offer a pay range of $30+ per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply.</p> <p>All candidates must pass an interview as part of the contracting process.</p>