Software Engineer, Rust

Software Engineer, RustBroomfield, Colorado, United StatesAnduril 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.What You Will Do:Define and influence the direction of a small team, leveraging your subject-matter expertise in target tracking and state estimation.Architect, maintain, and evolve complex software systems, refactoring existing codebases to improve performance, maintainability, and scalability.Prototype and deploy state-of-the-art algorithms for tracking, multi-sensor data fusion, and state estimation in agile, iterative development environments.Develop high-performance Rust software for real-time systems, ranging from tactical implementations to simulation environments and decision support tools.Design and implement robust filters, estimators, and probabilistic reasoning systems that enable actionable insights from noisy, ambiguous, or incomplete sensor data.Apply software design patterns and architectural best practices to manage technical debt and guide the evolution of production systems over time.Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate the benefits of our technology.Drive customer success by customizing algorithms and software for mission-critical use cases, including real-time tracking and sensor fusion.Integrate tracking and estimation technologies into the broader software development lifecycle, from requirements definition through testing and optimization.Translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues and end-users.Required Qualifications5+ years of professional software engineering experience & a Bachelor's degree in mathematics, physics, engineering, or other technical field (advanced degree strongly preferred)Demonstrated experience managing and evolving software architecture in production environments, including refactoring legacy systems and managing technical debt.At least 2+ years working on a single codebase or product, maintaining and expanding it as requirements evolved.Strong understanding of software design patterns, architectural principles, and best practices for building maintainable, scalable systems (beyond basic syntax proficiency).Proficiency in algorithm design, software development, and statistical modeling; experience with Rust, C/C++, Python, and Matlab is a plus.Solid understanding of applied mathematics, including linear algebra, optimization, probability, and stochastic processes.Knowledge of signal processing techniques for interpreting diverse sensor data (e.g., radar, lidar, EO/IR).Familiarity with big data pipelines, NoSQL databases, and the efficient handling of large-scale sensor data.Ability to engineer robust systems for estimation theory, adaptive filtering, controls, and complex signal environments.Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems.Eligible to obtain and maintain an active U.S. Secret security clearance.Preferred QualificationsExperience refactoring and modernizing Rust codebases in production environments.Track record of architectural decision-making and technical leadership on long-lived projects.Contributions to open-source Rust projects or the broader Rust ecosystem.Experience with concurrent and parallel programming patterns in Rust.Experience in state estimation, including Bayesian filtering, sensor fusion, and recursive estimation techniques.Background in machine learning as applied to target tracking and recognition, including clustering, classification, and anomaly detection techniques.Knowledge of target tracking techniques, such as Kalman filters, particle filters, and multi-target tracking algorithms (e.g., JPDA, MHT, or PHD filters).