Senior Software Engineer, Autonomy Capabilities
Design and deploy tactical autonomy algorithms and high-performance software for unmanned systems operating in complex, contested environments. The role requires 5+ years of related experience, strong C++ and Python skills, robotics expertise, and the ability to obtain a SECRET clearance.
About the job
Responsibilities
- Design tactical autonomy algorithms enabling unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
- Develop high-performance software modules for planning, decision-making, and behavior execution in dynamic and adversarial environments.
- Implement and test behavior architectures supporting multi-agent coordination, target engagement, reconnaissance, and survivability.
- Integrate classical autonomy with machine learning, including rule-based and reinforcement-learning methods.
- Collaborate with perception, planning, simulation, hardware, and flight-test teams to integrate autonomy solutions onto real-world platforms.
- Deploy capabilities to operational platforms and participate in field tests, flight demonstrations, and integration events.
- Analyze mission logs and performance data, diagnose failures, and optimize behavior models.
- Research and prototype algorithms, identify tactical capability gaps, and contribute to the autonomy roadmap.
- Adapt autonomy solutions to evolving defense program requirements, compliance needs, mission sets, and operational feedback.
- Travel approximately 10–15% annually.
Requirements
- Bachelor’s or master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a related field; equivalent practical experience may be considered.
- At least 5 years of related experience with a bachelor’s degree, 4 years with a master’s degree, or 2 years with a PhD; equivalent work experience may be considered.
- Proficiency in C++ and Python, with familiarity with real-time operating systems.
- Significant experience in one or more robotics areas, including control systems, motion planning, optimization, tactical behaviors, or distributed decision-making.
- Significant experience with unmanned systems and related algorithms, ideally in the space domain.
- Experience with simulation tools and environments such as AFSIM, NGTS, or similar platforms.
- Strong problem-solving and system troubleshooting skills.
- Excellent communication and collaboration skills in multidisciplinary environments.
- Ability to obtain a SECRET clearance or higher.
Nice-to-Haves
- Experience across multiple aerospace domains, including air, land, sea, or space.
- Experience spanning classical control, optimization, and applied machine learning or reinforcement learning.
- Background in collaborative behaviors and swarm robotics.
- Familiarity with defense or government programs.
- Hands-on experience supporting integration events, customer demonstrations, or live exercises.
Skills
C++, Python, Real-Time Operating Systems, Control Systems, Motion Planning, Optimization, Reinforcement Learning, Distributed Decision-Making, Unmanned Systems, Afsim, Ngts, Swarm Robotics, Machine Learning, Simulation
Similar jobs
ML Engineering jobs
Square
United States
Leads the design, deployment, and optimization of agentic and generative AI systems that automate risk and compliance investigations at scale. Requires 8+ years of machine learning modeling experience, production ML expertise, and advanced technical education.
Nuro
Mountain View, CABuild and operate large-scale infrastructure for autonomous-driving model training, including distributed GPU systems, data pipelines, ML workflows, and reliability tooling. The role requires 3+ years of experience, strong Python and systems-language skills, Kubernetes expertise, and distributed-systems fundamentals.
Traba
New York, NYBuild and deploy production AI-agent systems, including their harnesses, evaluations, orchestration, and supporting services. The role requires 5+ years of software engineering experience, production LLM or agent experience, and strong Python or TypeScript/Node.js skills.
Metriport
San Francisco, CA
Own machine learning end to end, from modeling messy clinical data through production deployment, monitoring, and infrastructure. The role requires 7+ years of experience building scalable ML systems, strong software and data engineering skills, and proficiency with Python, SQL, and cloud platforms.
SentiLink
United States
Leads and manages an applied machine learning team developing production fraud detection and identity verification models. The role combines people leadership with hands-on technical work and requires substantial ML experience, production deployment expertise, and experience in risk-focused domains.