Autonomy Engineer, Ops Research (Senior - Principal)

trueanomalyinc; Denver (CO); On-site; USD 180,000 - 360,000; Full time

Benefits offered by this job

Equity

Health benefits

Dental coverage

Vision care

HRA/HSA options

PTO

Paid holidays

401K

Parental Leave

Job summary

True Anomaly Inc. seeks engineers to design, build, and deploy core autonomy capabilities at the intersection of AI, ML, and optimization. You will work on fleet scheduling, vehicle autonomy, mission planning, wargaming, and threat assessment within a cross‑functional team.

You are a first principles engineer who owns the systems you build and delivers results in a real-time, high-stakes environment. A strong background in optimization and AI is essential.

Qualifications

• Bachelor's degree in a quantitative discipline.
• Proficient in C/C++ and Python for implementing optimization solvers.
• Strong expertise in adversarial optimization, mathematical programming, and statistical learning.

Responsibilities

• Design, implement, and validate optimization algorithms for fleet-level mission planning and resource allocation.
• Contribute to system architecture for large-scale distributed optimization problems.
• Collaborate with cross-functional teams to formalize requirements into mathematical programs and deploy scalable solutions.
• Tune and validate optimization models through simulation and hardware-in-the-loop testing.
• Develop production-quality implementations with rigorous documentation and testing.

Skills

C/C++

Python

Adversarial optimization

Mathematical programming

Statistical learning

Distributed optimization

Probability theory

Education

Bachelor's degree

Tools

Optimization solvers

Job description

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.

OUR MISSION

True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors - enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.

OUR VALUES

Be the offset. We create asymmetric advantages with creativity and ingenuity.

What would it take? We challenge assumptions to deliver ambitious results.

It's the people. Our team is our competitive advantage and we are better together.

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 fleet scheduling, 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 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

QUALIFICATIONS

• Bachelor's degree in operations research, applied mathematics, computer science, aerospace engineering, electrical engineering, or related quantitative discipline
• Proficient in C/C++ and Python for implementing optimization solvers and numerical methods
• Strong expertise in at least one domain:
  • 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

PREFERRED SKILLS AND EXPERIENCE

• Master's or PhD in operations research, applied mathematics, computer science, aerospace engineering, or related discipline
• Experience with high-performance numerical computing and production‑grade solver implementations
• Familiarity with edge computing constraints and real‑time optimization under latency bounds
• Background in astrodynamics, orbital mechanics, or spacecraft operations
• Experience with Bayesian inference, state estimation (Kalman filtering, particle methods), and planning under partial observability
• 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

COMPENSATION

Base Salary: $180,000 - $360,000

• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave

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.