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True Anomaly is building autonomous spacecraft, advanced payloads, mission software, and space-based interceptors to secure the space domain for the U.S. and its allies. As an Autonomy Engineer on the Applied Algorithms and Autonomy team, you will design, build, and deploy core autonomy capabilities at the intersection of artificial intelligence, machine learning, and classical optimization.
You will take ownership of systems spanning fleet scheduling, vehicle autonomy, mission planning, wargaming, threat assessment, and uncooperative rendezvous and proximity operations (RPO). Your responsibilities include:
- Design, implement, and validate optimization algorithms for fleet-level mission planning, resource allocation, and sequential decision-making under uncertainty
- Contribute to system architecture for large-scale distributed optimization problems, informed by statistical modeling, simulation-based analysis, and operational constraints
- Collaborate with cross-functional teams to formalize stakeholder requirements into mathematical programs and deploy scalable solutions
- Tune and validate optimization models through simulation, hardware-in-the-loop testing, and operational deployment
- Develop production-quality implementations with rigorous documentation and testing
You are a first-principles engineer who takes ownership and delivers results. The role requires a Bachelor's degree in operations research, applied mathematics, computer science, aerospace engineering, electrical engineering, or a related quantitative discipline. You must be proficient in C/C++ and Python for implementing optimization solvers and numerical methods, with strong fundamentals in optimization theory, algorithms, and software engineering practices.
