Full Stack Reinforcement Learning (RL) Engineer Specialist - Freelance Project
Agency
Posted: December 17, 2025
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Quick Summary
Design and implement reinforcement learning models and pipelines for dynamic environments and optimization problems, collaborating with engineers and data scientists to integrate RL models into production systems and interfaces.
Required Skills
Job Description
What You’ll Do
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.
• Develop RL Models and Pipelines: Design, train, and evaluate reinforcement learning models tailored to dynamic environments and optimization problems.
• Application Integration: Collaborate with engineers and data scientists to integrate RL models into production systems and interfaces, ensuring usability and performance.
• Full Stack Contribution: Contribute to backend services, APIs, and React-based frontends supporting RL experiments and applications.
• Data Exploration and Experimentation: Work with large-scale datasets and simulation environments to inform model development and evaluation.
What We Need
Professional Experience:
• 3+ years of experience building and deploying ML systems, with at least 1+ year focused on reinforcement learning.
• Background contributing to both backend and frontend components of production-grade systems.
• Experience engaging with stakeholders or project teams to refine requirements and translate into technical deliverables.
Technical Expertise:
• Strong programming skills in Python and JavaScript (or similar), with proficiency in frameworks such as PyTorch, TensorFlow, or JAX for RL.
• Familiarity with RL libraries and environments (e.g., OpenAI Gym, RLlib, Stable Baselines, custom simulators).
• Experience with backend frameworks (FastAPI, Flask, or similar) and frontend frameworks (React, Vue, or similar).
• Comfort with containerization and cloud environments (GCP, AWS, or similar).
• Understanding of distributed training, scaling RL systems, and experiment tracking.
• Ability to produce clean, modular, and testable code in collaborative environments.
Important:
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.
All candidates must pass an interview as part of the contracting process.