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Software Engineer; C++

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Applied Intuition
Full Time position
Listed on 2026-06-02
Job specializations:
  • Software Development
    Software Engineer, Robotics, Embedded Software Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer (C++)

Requirements

  • Bachelor’s in Computer Science, Mathematics, or related field
  • 1+ years of experience in shipping complex software in C++11 and above
  • (Desirable) A MSc or PhD in computer science or applied mathematics with coursework or research experience in robotics
  • (Desirable) Experience developing onboard or embedded application software (e.g., autonomy, ADAS, robotics)
  • (Desirable) Experience with driver assistance or autonomous driving systems or off-road products
  • Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
What the job involves
  • The Onboard Architecture Team is responsible for full autonomy stack onboard architecture—ensuring every component works cohesively, reliably, and safely
  • Our team is looking for C++ software engineers interested in designing elegant solutions to difficult problems within autonomous systems and robotics
  • You will focus on application‑level onboard software in a modern C++ codebase working across our suite of products, tackling difficult problems
  • If you're motivated by complex systems, ownership across boundaries, and real-world impact, this is where architecture meets autonomy
  • Design and implement onboard application software in modern C++ for state and mode management (mission manager) on vehicle compute
  • Collaborate with cross functional teams to align interfaces, contracts, and execution models across the stack
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