Lead Space Autonomy Engineer - Operations Research

Socket.dev; Denver (CO); On-site; USD 180,000 - 360,000; Full time

Job summary

True Anomaly in Denver/Long Beach is seeking a seasoned optimization engineer to design, implement, and deploy core autonomy capabilities for space missions. You will collaborate with a cross-functional team to advance technology at the intersection of artificial intelligence, machine learning, and classical optimization, focusing on fleet scheduling, vehicle autonomy, and mission planning.

This role requires hands-on development, strong mathematical programming skills, and a track record

Qualifications

• Bachelor's degree in a quantitative discipline such as OR, math, CS, aerospace, or EE.
• Proficient in C/C++ and Python for optimization solvers.
• Experience with optimization across fleet scheduling and mission planning.
• Knowledge of game theory, Nash equilibria, minimax optimization.
• Familiarity with model predictive control and trajectory optimization.
• Experience deploying optimization in operational systems with real-world constraints.
• Strong collaboration across disciplines to translate problems into math programs.
• Interest in space operations and autonomy.

Responsibilities

• Design and validate optimization algorithms for fleet-level planning under uncertainty.
• Contribute to large-scale distributed optimization architectures.
• Collaborate to translate stakeholder requirements into mathematical programs.
• Tune models through simulation and hardware-in-the-loop testing.
• Develop production-quality implementations with documentation and testing.

Job description

True Anomaly in Denver/Long Beach is seeking a seasoned optimization engineer to design, implement, and deploy core autonomy capabilities for space missions. You will collaborate with a cross-functional team to advance technology at the intersection of artificial intelligence, machine learning, and classical optimization, focusing on fleet scheduling, vehicle autonomy, and mission planning.

This role requires hands-on development, strong mathematical programming skills, and a track record