RL/ML Software Engineer
Description For RL/ML Software Engineer
EpiSci is at the forefront of tactical mission autonomy, combining cutting-edge AI, autonomy algorithms, and wireless communications to address critical national security challenges. As an RL/ML Software Engineer on the Cognitive Sensing and Radio Frequency team, you'll be instrumental in developing state-of-the-art estimation and adaptive control algorithms.
The role demands expertise in reinforcement learning and machine learning, with a focus on developing solutions for multi-agent systems and unmanned aerial vehicles (UAVs). You'll be working on sophisticated projects that include AI implementation in aircraft like F-22 and F-16, revolutionizing tactical communication systems, and developing autonomous UAV swarms enhanced by sensor fusion.
Key responsibilities include developing novel reinforcement learning algorithms, creating simulated models for tactical military missions, and implementing adaptive control theory. The position requires a Master's or PhD in machine learning/reinforcement learning with robotics applications, strong programming skills in C++/Python, and experience with containerized development environments.
This is an exciting opportunity for someone passionate about applying advanced AI technologies to real-world defense applications. You'll be working on cutting-edge projects that directly impact national security, with the chance to see your work deployed in actual field operations. The role offers competitive compensation ($150,000-$180,000) and the opportunity to work on challenging technical problems with significant real-world impact.
As a U.S. citizen-required position, you'll be part of a team pushing the boundaries of what's possible in tactical AI and autonomous systems. The role involves occasional travel (~10%) for project implementation and field testing, offering hands-on experience with the technologies you'll be developing.
Responsibilities For RL/ML Software Engineer
- Develop novel model-based reinforcement learning algorithms for multi-agent systems
- Integrate and deploy algorithms for integration and field testing events
- Write autonomy software that operates group 1-5 unmanned aerial vehicles (UAVs)
- Create simulated models to accomplish tactical military missions
- Design models that use techniques from adaptive control theory and estimation
Requirements For RL/ML Software Engineer
- Master's or PhD degree in machine learning/reinforcement learning with autonomy and robotics applications
- Experience developing model-based and model-free reinforcement learning algorithms
- Hands on experience of behavior prediction, intent estimation and behavior prediction
- Experience taking new autonomy capabilities from ideation through fielding
- Experience developing in Docker and containerized development environments
- Strong programming skills in C, C++, and Python, Linux-based operating systems
- Must be a U.S. Citizen
- Must be willing to travel (~10% of time)
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