Signal Processing Engineer, Space
Anduril IndustriesWashington, District of Columbia, United StatesPosted 21 April 2026
Tech Stack
Job Description
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.
ABOUT THE TEAM
Anduril's Space team is dedicated to expanding our AI-powered capabilities into the final frontier, enhancing Space Domain Awareness, Space Control, and Command and Control for U.S. military and allied partners. We're developing fully integrated hardware and software systems, including Lattice for Space Missions and modular payloads, to address growing threats in space and ensure our Guardians maintain a decisive advantage in this contested war-fighting domain.
ABOUT THE JOB
We are looking for a Signal Processing Engineer to join our rapidly growing team in Washington DC. In this role, you will be responsible for developing discrimination algorithms that separate threats from non-threats, decoys, and debris using EO/IR sensor data for space and missile defense missions. You will design signal processing pipelines including detection, feature extraction, image processing, and develop advanced decision logic to enhance classification performance. This will require deep expertise in signal processing for EO/IR sensors, classification algorithms, detection theory, and proficiency in algorithm development. If you are someone who loves the challenge of extracting signal from noise, thrives on building algorithms that work in contested and degraded environments, and wants to see your work protecting forces against emerging threats in space, then this role is for you.
WHAT YOU’LL DO
Develop discrimination algorithms for EO/IR sensors that classify and distinguish threats from decoys, debris, and clutter in real-time operational environments
Design and implement signal processing pipelines including detection algorithms, feature extraction, image processing, and measurement generation from sensor data
Develop and integrate advanced decision logic to enhance classification performance and adapt to evolving threat environments
Analyze and optimize algorithms for EO/IR sensor phenomenology including noise characteristics, SNR considerations, resolution limits, and environmental effects
Build physics-based models and conduct modeling and simulation including Monte Carlo analysis, recorded sensor playback, and hardware-in-the-loop testing to validate discrimination performance
Develop analysis tools to characterize discrimination algorithm performance under challenging conditions such as countermeasures, clutter, and degraded sensing environments
Collaborate with software engineers to transition discrimination algorithms from prototypes to production code optimized for operational deployment
Engage with customers and stakeholders to understand mission needs, present discrimination solutions, and demonstrate system performance
REQUIRED QUALIFICATIONS
Currently possesses and is able to maintain an active U.S. Secret security clearance
Bachelor's degree or higher in Electrical Engineering, Computer Engineering, Aerospace Engineering, Applied Mathematics, Physics, Computer Science, or a related technical field
5+ years of experience designing, implementing, and testing signal processing algorithms for EO/IR sensors or similar sensing modalities in aerospace or defense systems
Strong understanding of EO/IR sensor phenomenology including noise characteristics, detection theory, SNR analysis, resolution l ... (truncated, view full listing at source)
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