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Anduril Industries

Software Engineer, Battlespace Awareness

Waltham, Massachusetts, United StatesFrom $253kmidAdded 1 month ago

About this role

Anduril Industries is looking for a Software Engineer for their Battlespace Awareness team in Waltham, MA. The role involves developing cutting-edge algorithms and software to enhance military operations, requiring strong technical skills and collaboration with innovative teams.

What you'll do

  • Contribute expertise and ideas within a small team
  • Prototype advanced software solutions
  • Implement high-performance software for tactical systems and web applications
  • Utilize modeling and simulation to assess technology benefits
  • Engage with customers for mission-critical project success
  • Involve in all aspects of the software development lifecycle

What they're looking for

  • 5+ years of software engineering experience
  • Bachelor's degree in a technical field (advanced degree preferred)
  • Proficiency in C/C++, Python, and Matlab
  • Experience with big data/NoSQL technologies
  • Knowledge of software design and algorithm implementation
  • Machine learning techniques
  • Applied mathematics skills
  • Familiarity with controls and digital signal processing

Benefits

  • Highly competitive salary range ($191,000 - $253,000 USD)
  • Competitive equity grants
  • Top-tier benefits for full-time employees
  • [unknown]
  • [unknown]
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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.

View all jobs at Anduril Industries

Likely interview questions

  • Walk us through a complex C++ or Python project where you implemented a high-performance algorithm. How did you approach optimization and testing?
  • Describe your experience with machine learning—specifically, have you built supervised or unsupervised learning models, and how did you evaluate their performance?