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Waltham, Massachusetts, United States
Onsite
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
At Anduril, our Battelspace Awareness Command and Control Software team specializes in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. Operating in small, innovative teams, we push the boundaries of what's possible to deliver advanced technologies with mission-critical applications. Our commitment doesn't end with academic research or proof-of-concept experiments; we measure our success by the real-world impact of our deployed solutions. Inspired by Arthur C. Clarke's vision — "Any sufficiently advanced technology is indistinguishable from magic" — we aim to achieve groundbreaking results in path planning, route optimization, and autonomous mission execution at the command and control layer. We are currently seeking highly talented technologists to join our mission and redefine the future of defense technology.
Define and influence the direction of a small team within the Command and Control Software organization, leveraging your subject-matter expertise in path planning and route optimization.
Prototype and deploy state-of-the-art algorithms for global and local path planning, trajectory optimization, and multi-agent coordination within command and control systems.
Develop high-performance software for real-time C2 systems, ranging from operator-facing mission planning tools to autonomous tasking and routing services that orchestrate fleets of unmanned platforms.
Design and implement robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments.
Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate planner behavior across diverse mission scenarios.
Drive customer success by customizing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance.
Integrate path planning technologies into the broader command and control software stack and development lifecycle, from requirements definition through testing and optimization.
Translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues, operators, and end-users.
8+ years of experience in algorithm design, software development, and mathematical modeling with programming expertise in C/C++, Python, and Matlab.
Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling-based planners (RRT, RRT*, PRM), and lattice or grid-based planners.
Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6-DoF simulation, intercept analysis).
Solid understanding of applied mathematics, including linear algebra, optimization, computational geometry, and graph theory.
Knowledge of vehicle dynamics, kinematic constraints, and control theory as applied to autonomous ground, air, or maritime platforms tasked through C2 systems.
Familiarity with map representations, terrain reasoning, and the efficient handling of large-scale geospatial and environmental data within distributed C2 architectures.
Background in machine learning as applied to planning and decision-making, including reinforcement learning, learned heuristics, and behavior prediction.
Ability to engineer robust systems for planning under uncertainty, multi-agent coordination, and operation in complex, dynamic, contested environments.
Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems.
Eligible to obtain and maintain an active U.S. Top Secret security clearance.
We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
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