ML Perception Software Engineer

About the role

We are looking for a software engineer with expertise in perception for autonomous vehicles or mobile robots. Your contributions will focus on building out key capabilities of perception modules within an autonomous vehicle stack, such as building 4D world representations to support end-to-end autonomy. You will also drive the design and development of computer vision and machine learning techniques to enable self-driving vehicles to navigate. In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the nascent autonomy industry. We move fast and focus on excellence, for our products and for our business. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied Intuition is the place for you! We are hiring for all levels. At Applied Intuition, you will: 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 We're looking for someone who has: 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.

Requirements

• MSc or PhD in perception or closely related field
• Experience working in modern ML-based perception for autonomous systems
• Deep knowledge of the current trends in computer vision including perception, reconstruction, diffusion, world models and pre training vision models.
• Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $125,000 - $222,000 USD annually.
• 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 d

Benefits

Additional Information

About Applied Intuition 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.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co . We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. Hear from an Engineer:

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