ML Perception Software Engineer
Applied Intuition is seeking a Machine Learning Perception Software Engineer to enhance the perception modules within our autonomous vehicle stack. This role involves developing advanced algorithms to construct comprehensive world representations, supporting end-to-end autonomy solutions. As part of our dynamic team, you will contribute to the advancement of self-driving technologies in a fast-paced environment focused on excellence.
Key responsibilities include designing and implementing state-of-the-art algorithms for perception, world modeling, and machine learning-driven autonomy. You will test and evaluate these algorithms on real vehicles, taking ownership of significant portions of the autonomy stack to ensure tangible improvements in driving capabilities. Collaboration with data, behavior, and research teams is essential to develop and deploy cutting-edge autonomy software for our customers.
The ideal candidate possesses a Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a related field, with over three years of experience addressing real-world perception challenges. Proficiency in C++ and Python is required, along with experience in building machine learning models from data collection to production deployment. A deep understanding of relevant frameworks and libraries, coupled with a keen interest in staying abreast of industry trends, is highly valued.
Compensation for this full-time, on-site position in Sunnyvale, California, ranges from $125,000 to $222,000 annually, depending on experience and qualifications. The package includes equity options and comprehensive benefits such as health, dental, vision, life, and disability insurance, 401(k) retirement plans with employer match, learning and wellness stipends, and paid time off.
Applied Intuition fosters a collaborative and customer-focused culture, emphasizing rapid innovation and excellence. Employees are encouraged to manage their schedules responsibly, with flexibility for occasional remote work to accommodate personal commitments. This environment offers significant growth opportunities for individuals passionate about advancing autonomous systems and making a substantial impact in the field.