Reinforcement Learning AI Engineer
$99,000–$225,000 year
HybridMcLean, Virginia, United States or Colorado Springs, Colorado, United States
Job Summary
Design, implement, and train reinforcement learning and multi-agent reinforcement learning algorithms for complex decision-making problems. Develop scalable training pipelines using Python and modern ML frameworks, then build and evaluate agents in simulated environments using Gym, PettingZoo, or high-fidelity simulators. Apply techniques such as policy optimization, value-based learning, and imitation learning while collaborating with domain experts to define reward structures aligned with mission objectives. Transition trained models into production systems following strong software engineering best practices, contributing to system architecture and performance optimization in Python with opportunities to extend into C++ or Rust.
Required Qualifications
- 3+ years of experience developing and training RL agents
- Experience with AI, data science, ML engineering, or software engineering
- Experience with Gym or PettingZoo interfaces
- Experience with ML frameworks such as PyTorch, TensorFlow, or JAX
- Experience developing technical solutions using Rust, Python, or C++
- Knowledge of RL and artificial neural networks
- Ability to travel up to 25% of the time
- Secret clearance
- Bachelor's degree in a CS, AI, or Engineering field
Desired Qualifications
- Experience applying RL to autonomy, control systems, or mission-scale
- Experience with MARL
- Experience with AFSIM or other high-fidelity simulation environments
- Experience with embedded systems programming in Rust, C, or C++
- Experience in GPU programming, including CUDA or RAPID
- Experience developing in-space solutions
- Knowledge of modern software design patterns, including microservice design and orchestration in Kubernetes deployment
- Master's degree in CS, AI, Engineering, or a related field
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.