Anduril Industries
Software Engineer, Battlespace Awareness
About this role
Anduril Industries is looking for a Software Engineer for its Battlespace Awareness team, focused on advancing military technologies using state-of-the-art software and algorithms. The role involves collaborating in small teams to develop solutions that enhance mission-critical systems, utilizing cutting-edge techniques in AI and software development.
What you'll do
- Guide a small team with expertise and innovative ideas
- Prototype advanced software solutions in an agile setting
- Develop high-performance software for various applications
- Utilize modeling and simulation tools to analyze technology benefits
- Engage with customers to meet mission-critical objectives
- Oversee all phases of the software development lifecycle
What they're looking for
- Experience in software engineering (2+ years)
- Proficiency in C/C++, Rust, Python, and Matlab
- Knowledge of big data and NoSQL technologies
- Solid understanding of software design and algorithms
- Familiarity with machine learning techniques
- Applied mathematics skills
- Engineering principles in controls and signal processing
- Eligibility for a U.S. Top Secret SCI security clearance
Benefits
- Competitive salary range ($126,000 - $167,000)
- Equity grants
- Top-tier benefits package
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Anduril Industries
Anduril Industries builds autonomous defense systems including underwater vehicles, unmanned aircraft, and electronic warfare platforms for the Department of Defense. The company is hiring across mechanical engineering, mission operations, software development, technical leadership, and advanced manufacturing roles to support the design, deployment, and production of these mission-critical systems.
- Website
- anduril.com
Likely interview questions
- Walk us through a project where you implemented a high-performance software system. What were the key performance bottlenecks and how did you optimize for them?
- Describe your experience with C/C++, Rust, and Python. Which have you used most extensively and in what contexts—particularly for systems-level vs. application-level work?