Autonomy Engineer (Senior - Principal)

YOUR MISSION

As a member of the Applied Algorithms and Autonomy team, you will design, build, and deploy core autonomy capabilities for True Anomaly. You will work with a talented cross-functional team to advance technology at the intersection of artificial intelligence, machine learning, and classical optimization. This will involve hands-on development across various areas including vehicle autonomy, mission planning, wargaming, threat assessment, and uncooperative RPO capabilities. You are a first principles engineer who takes ownership of the systems you build and delivers results. 

RESPONSIBILITIES

• Design, implement, and test algorithms that enable autonomous mission planning, tasking, and decision-making 
• Contribute to autonomy architecture discussions and implement robust solutions informed by statistical analysis, software testing, and hardware-in-the-loop simulation 
• Collaborate with cross-functional teams to translate requirements and stakeholder expectations into production-ready autonomy solutions 
• Debug and tune autonomy systems through integration, testing, and deployment in real-world operational environments 
• Write clean, well-documented, and testable code in support of autonomy capabilities 

QUALIFICATIONS

• Bachelor's degree in computer science, robotics, aerospace engineering, electrical engineering, or a similar discipline 
• Proficient in C/C++ and Python 
• Strong understanding of at least one of technologies within the four pillars: 
  • Adversarial planning: classical game theory, self-play, counterfactual regret minimization, Monte Carlo tree search, behavior trees, etc. 
  • Classical optimization: MPC, trajectory optimization, dynamic programming, stochastic control, mixed integer programming, quadratic programming, etc. 
  • ML/AI: reinforcement learning, imitation learning, transformer architectures, anomaly detection, classification/regression, behavior modeling, etc. 
  • Multi-Agent Control: multi-agent coordination, consensus algorithms, networked control systems, communication-aware planning, fault detection & isolation 
• Solid foundation in statistics, optimization, and decision-making under uncertainty 
• 4+ years of experience implementing algorithms to support autonomous planning and decision-making deployed in real-world systems 
• Demonstrated ability to work in a multidisciplinary team and solve complex problems with first principles approaches 
• Passion for spaceflight and advancing capabilities related to space domain awareness and space security 

PREFERRED SKILLS AND EXPERIENCE

• Master's or PhD in computer science, robotics, aerospace engineering, electrical engineering, or a similar discipline 
• Experience writing high-reliability, production C/C++ code 
• Experience with edge computing and real-time processing constraints 
• Experience with space systems (orbital mechanics, GNC, spacecraft operations) 
• Familiarity with probabilistic reasoning, state estimation (EKF/UKF, particle filters), and planning under uncertainty 
• Background in verification/validation of autonomous systems for certification or operational deployment 
• A understanding of how game theory, optimization and AI can be fused together.

COMPENSATION

• Base Salary: $180,000 - $360,000
• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. 

ADDITIONAL REQUIREMENTS

• Work Location—This is a fully onsite role. Candidates must be based in or able to commute to our Denver or Long Beach office daily.
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below. #LI-Onsite