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# Senior Mission Autonomy Software Engineer - Space Systems

- **Company:** Trusted Inc.
- **Location:** United States
- **Experience:** Expert
- **Salary:** $135,000 - $225,000
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Algorithm Design, Systems Engineering, Automation of Tests, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Software Architecture, Software Engineering, Software Systems, Data Streaming, Systems Integration, Reinforcement Learning, Information Technology
- **Published:** November 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=709131ef9cf204cf

## About the Role

* United States Citizenship required.
 * Bachelor's degree in computer science, engineering, mathematics, physics, or another relevant technical field and 5+ years of professional software engineering experience, or 9+ years of relevant professional experience in lieu of a degree, including significant experience developing algorithmic, autonomy, robotics, optimization, controls, or other technically complex software systems.
 * Strong Python software development skills, with experience building maintainable, production-quality software within large or evolving codebases.
 * Demonstrated ability to understand and implement mathematically or algorithmically complex methods, including the ability to diagnose performance issues, tune behavior, and make sound implementation tradeoffs.
 * Experience taking algorithms, models, or technical prototypes from early-stage implementation into integrated, tested, and reliable software capabilities.
 * Experience with simulation, automated testing, performance evaluation, and debugging of complex software or algorithmic systems.
 * Ability to work independently on ambiguous technical problems, make architecture and implementation decisions, and drive capabilities through integration and delivery.
 * Strong communication and collaboration skills, including the ability to work effectively with researchers, software engineers, systems engineers, and technical subject-matter experts.
 * Ability to work collaboratively in cross-functional Agile teams.

Desired Skills and Experience

 * Experience from one of the following domains: autonomy, robotics, UAVs, reinforcements learning, optimization, model predictive control, planning, decision- making, or related techniques.
 * Hands-on experience training, tuning, and evaluating reinforcement learning policies or other machine learning or autonomy algorithms.
 * Experience developing software for space, aerospace, defense, robotics, or other mission-critical systems.
 * Familiarity with distributed systems, simulation environments, message-based architectures, or integration of software across multiple system components.
 * Experience supporting technical demonstrations, system-level verification and validation, or operational deployment of complex software capabilities.
 * Active security clearance or prior experience working in classified environments.

## Description

Trusted Space is seeking a Senior Autonomy Engineer to build and integrate autonomy algorithms and support performance evaluation in simulation and demonstration environments., * Own the transition of autonomy capabilities from R&D prototypes to operational software, including implementation, integration, tuning, validation, and readiness for mission use.

 * Develop robust, maintainable Python/Rust software for autonomy, planning, decision-making, optimization, and control capabilities within a larger mission software stack.
 * Serve as a technical owner for autonomy performance in the integrated system, understanding algorithm behavior deeply enough to tune parameters, diagnose unexpected behavior, and drive performance and reliability issues to resolution.
 * Integrate autonomy capabilities with mission software, simulations, external services, and system interfaces, troubleshooting issues across algorithms, software components, interfaces, and data flows.
 * Define and drive the testing and evaluation approach for autonomy capabilities, including simulation scenarios, automated testing, performance metrics, acceptance criteria, and evaluation tooling across nominal, off-nominal, and edge-case conditions.
 * Train, evaluate, and tune reinforcement learning policies and other autonomy algorithms using established methods and architectures, including developing the workflows needed to analyze, compare, and improve training outcomes.
 * Partner closely with autonomy researchers and subject-matter experts to understand algorithm design, assumptions, reward structures, and failure modes, and make sound implementation and productization decisions as capabilities transition into production.
 * Own key aspects of the autonomy capability lifecycle, including software architecture, end-to-end system integration, mission demonstrations, and technical documentation, ensuring capabilities can be reliably deployed, maintained, and extended across missions.