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Applied Intuition

Robot type
Autonomous Vehicle · Robot AI and Software
Location
SunnyvaleCaliforniaUSA
Job type
Artificial Intelligence
Posted
Sep 8, 2024
Salary
$190,000–$352,000 a year
Full-time

ML Perception Software Engineer

Job description

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.;

Job responsibilities

  • Train, modify, and create beyond-SOTA algorithms for constructing powerful world representations that can be used for perception, world modeling, and ML driven autonomy
  • Test and evaluate your algorithms on real vehicles, owning large portions of the autonomy stack and ensuring that they provide real improvements to the driving abilities
  • Work closely with our data, behavior, and research teams to develop the most advanced autonomy software for all domains to deploy to production for our customers

Job requirements

  • 3+ years of experience building software components or (sub) systems that address real-world perception challenges
  • Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field
  • Strong proficiency in C++ and Python
  • Experience building machine learning models from data collection to production and deployment
  • Deep understanding of the concepts and methods behind any frameworks or libraries that they worked with
  • Interest in keeping up to date in their field, identifying trends and figuring out which new ideas are promising and which are risky.

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