Staff Engineer, Reinforcement Learning (R3639)

Founded in 2015, Shield AI is a venture-backed defense technology company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices in San Diego, Dallas, Washington, D.C., Boston, Abu Dhabi (UAE), Kyiv (Ukraine), and Melbourne (Australia), Shield AI’s technology actively supports U.S. and allied operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn,X, YouTubeand Instagram.     
JOB DESCRIPTION:
Founded in 2015, Shield AI is a venture-backed defense technology company with the mission of protecting service members and civilians with intelligent, autonomous systems. Its products include Hivemind Enterprise—EdgeOS, Pilot, Commander, and Forge—as well as V-BAT and Sentient Vision Systems (wide-area motion imaging software). With offices in San Diego, Dallas, Washington, D.C., Abu Dhabi (UAE), Kyiv (Ukraine), and Melbourne (Australia), Shield AI’s technology actively supports U.S. and allied operations worldwide.  For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X and Instagram.    
The Hivemind Pilot team is an agile group of engineers focused on building a state-of-the-art Autonomy Software Development Kit (SDK) that enables resilient autonomy and intelligence for a wide range of platforms in diverse environments. The Behavior and Motion Planning team in Pilot develops and integrates algorithms that enable robots to make smart decisions and navigate safely. The team also rigorously tests these systems to ensure reliable performance in real-world environments. 
As a member of Behavior and Motion planning team, you will leverage your expertise in robotics and Reinforcement Learning (RL) to develop, deploy, and optimize models for autonomous systems that operate in complex, real-world environments. You will collaborate with cross-functional teams to deliver robust, scalable solutions that advance the state of Hivemind SDK. You will also contribute to developing technical requirements, test plans, and validating the performance of algorithms and models. 

What You'll Do:

• Design, implement, and deploy reinforcement learning algorithms for a variety of platforms 
• Collaborate with teams across the organization to integrate RL solutions that meet customer specifications 
• Analyze and optimize performance of deployed RL models in dynamic environments  
• Develop tools and infrastructure to support large-scale training, simulation, and evaluation  
• Mentor and provide technical guidance to junior engineers  
• Stay current with the latest advancements in RL, and apply them to solve challenging problems  
• Contribute to the design and architecture of scalable, maintainable software systems 

Required Qualifications:

• Master's degree in Computer Science, Robotics, or a related field and 5+ years of relevant professional experience or PhD with 4+ years of relevant experience. 
• Familiarity with prototyping in Python is welcome, but this role demands professional C++ production deployment skills. Candidates whose primary experience is in Python are unlikely to find this position a good fit. 
• Demonstrated experience deploying reinforcement learning algorithms in production environments  
• Strong background deploying RL algorithms in production following full Software development lifecycle 
• Ability to independently deploy high-reliability code suitable for real-world autonomous systems 
• Experience with RL frameworks (e.g., TensorFlow (C++), libtorch, etc.) and RL training environments (e.g., OpenAI Gymnasium, Google DeepMind Control Suite, etc.) 
• Solid understanding of software engineering best practices, including version control, testing, and CI/CD  
• Familiarity with CUDA 
• Excellent problem-solving and communication skills 

Preferred Qualifications:

• Peer reviewed publications related to RL  
• Strong background in Robotics or autonomous systems 
• Experience with multi-agent RL or distributed RL systems  
• Familiarity with simulation environments (e.g. Isaac Sim, MuJoCo)  
• Experience with cloud-based training and deployment  
• Experience working in aviation, or other safety-critical domains 

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Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer