Senior Autonomy Software Engineer

• Serve as the Responsible Engineer for the autonomy and perception stack.
• Develop greenfield autonomy software from initial requirements and architecture through field-tested, production-ready implementation.
• Own autonomy behavior across mission planning, path planning, localization, state estimation, sensor fusion, perception, obstacle avoidance, recovery behavior, and fault-aware decision-making.
• Design and implement algorithms for object detection, recognition, classification, tracking, mapping, navigation, and autonomous decision-making.
• Develop both machine-learning-based and classical perception approaches, selecting the appropriate method based on mission requirements, data availability, compute constraints, reliability, and test evidence.
• Train, validate, evaluate, and improve perception and autonomy models using real, simulated, and replayed data.
• Build and maintain data workflows for model evaluation, scenario replay, regression testing, performance analysis, and failure investigation.
• Write, review, test, profile, and debug production software in appropriate systems and autonomy-development languages.
• Use modern machine learning frameworks for model development, training, evaluation, and deployment.
• Develop performance-conscious autonomy software under real-world compute, latency, memory, power, reliability, and observability constraints.
• Collaborate with Avionics engineers on sensor selection, sensing architecture, sensor trade studies, and practical perception requirements.
• Collaborate with Embedded Software engineers on platform integration, sensor interfaces, data pipelines, timing, logging, diagnostics, and deployment.
• Work with Test Engineering to validate autonomy behavior in simulation, laboratory, field, and sea-trial environments.
• Develop and maintain autonomy test environments, including:
• HOOTL — hardware-out-of-the-loop / SIL — software-in-the-loop
• HIL/HITL — hardware-in-the-loop
• Scenario-based simulation and replay
• Model validation and regression testing
• Analyze vehicle behavior from logs, telemetry, simulation results, field tests, and sea trials to identify root causes and drive corrective improvements.
• Define metrics for autonomy performance, perception quality, model reliability, mission success, and failure modes.
• Build automated development workflows using modern build systems, continuous integration, static analysis, profiling, model-evaluation pipelines, and automated testing.
• Produce concise, functional engineering documentation that enables implementation, testing, operation, and future development.
• Use AI-assisted development tools to accelerate implementation, testing, debugging, data analysis, and documentation while independently validating outputs and maintaining a first-principles understanding of the resulting system.
• Mentor other engineers and contribute to technical reviews without moving away from hands-on engineering.

• Deep practical experience developing autonomy, perception, planning, or robotics software for real-world systems.
• Strong proficiency in at least one systems programming language.
• Strong proficiency in a scripting language commonly used for autonomy development, data analysis, model development, testing, and automation.
• Experience with machine learning or deep learning for perception, classification, detection, tracking, recognition, or related autonomy tasks.
• Experience with classical computer vision, machine vision, state estimation, localization, sensor fusion, or related non-ML perception methods.
• Experience with path planning, motion planning, obstacle avoidance, mission planning, behavior trees, state machines, or other autonomous decision-making approaches.
• Experience integrating autonomy software into real systems with imperfect sensors, incomplete requirements, constrained compute, noisy data, and difficult operating environments.
• Experience training, validating, evaluating, and improving models using structured metrics, test datasets, simulation, replay, and field data.
• Experience developing reliable production software, not just prototypes, research code, notebooks, or isolated algorithms.
• Experience writing maintainable code, conducting code reviews, developing automated tests, using static analysis, profiling performance, and debugging complex system behavior.
• Experience building or extending simulation, replay, SIL, HIL/HITL, or scenario-based test environments for autonomy validation.
• Ability to reason from first principles about autonomy failures, perception failures, sensor limitations, edge cases, and system-level behavior.
• Ability to work from incomplete information, make defensible technical decisions, and rapidly iterate between design, implementation, testing, and refinement.
• Ability to work independently with minimal oversight while collaborating closely across engineering disciplines.
• Willingness to support field testing and sea trials when required.

Approximately five or more years of relevant autonomy, perception, robotics, machine-learning, or production software experience is preferred, but demonstrated technical depth, multidisciplinary problem-solving ability, and a record of delivering difficult systems matter more than a specific number of years.

Exceptional candidates at any experience level are encouraged to apply.

• Autonomous vehicles, unmanned systems, UAVs, underwater systems, maritime systems, drones, robotics, aerospace systems, self-driving vehicles, industrial autonomy, or other real-world autonomous platforms.
• Taking autonomy, perception, planning, or machine-learning software from early architecture through field-tested deployment.
• Developing safety-critical, mission-critical, or high-reliability software for systems that operate in difficult real-world environments.
• Working with a range of perception and navigation sensing technologies.
• Developing autonomy software for GPS-denied, communications-constrained, low-observability, or otherwise challenging operating environments.
• Machine-learning model development, training, evaluation, deployment, or optimization using modern frameworks.
• Building simulation, replay, synthetic-data, scenario-generation, Monte Carlo, SIL, HIL/HITL, or model-validation environments for autonomy development.
• Debugging autonomy behavior using logs, telemetry, visualization tools, field data, and post-mission analysis.
• Working closely with electrical, embedded software, mechanical, manufacturing, and test engineers on tightly integrated electromechanical systems.

Odin Dynamics, Inc. participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Odin Dynamics is an equal opportunity employer committed to creating a diverse and inclusive workplace. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws.