Hiring: Autonomy Engineer, Ops Research (Senior - Principal) Company: True Anomaly Location: Long Beach, CA Job Posted Time: 2026-09-13 10:29:05 Employment Type: On-site Target Skills & Keywords : AI, C, C++, Machine Learning, Python, Reinforcement Learning About the job Experience: •Operational familiarity with edge computing constraints and real-time optimization under latency bounds •Background in astrodynamics, orbital mechanics, or spacecraft operations •Track record in verification/validation of mission-critical optimization systems •Understanding of how game-theoretic, optimization, and learning-based approaches compose for robust decision-making Required Skills: •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 •Partner cross-functionally 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 Qualifications: •Bachelor's degree in operations research, applied mathematics, computer science, aerospace engineering, electrical engineering, or related quantitative discipline, plus 8-11 years of experience; or a Master's degree in one of these fields with 6 years of experience; or a PhD with 3 years of experience. •Proficient in C/C++ and Python for implementing optimization solvers and numerical methods •Adversarial optimization: game theory, Nash equilibria, minimax optimization, sequential games, adversarial search •Mathematical programming: model predictive control, trajectory optimization, dynamic programming, stochastic control, mixed-integer programming, convex optimization •Statistical learning: reinforcement learning, online learning, classification/regression under uncertainty, anomaly detection, predictive modeling •Distributed optimization: fleet coordination, consensus protocols, multi-agent resource allocation, network flow optimization, decentralized control •Solid foundation in probability theory, optimization, and stochastic decision processes •4+ years implementing and deploying optimization algorithms in operational systems with real-world constraints •Demonstrated ability to formulate complex problems as tractable mathematical programs and collaborate across disciplines •Passion for space operations and advancing capabilities in space domain awareness Compensation: •$180,000 - $360,000 / year •Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!