Rivian
Staff Machine Learning Engineer, End-to-End Autonomy
Palo Alto, California, USA · Staff+ · Full-time
Sponsorship not specified$228k-$285kDetected 29 days ago
Machine LearningNLPCorporate LawCommunicationMentoring
About the role
- As a company, we constantly challenge what's possible, never simply accepting what has always been done.
- We reframe old problems, seek new solutions and operate comfortably in areas that are unknown.
- Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Responsibilities
- This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
- This model will support not only decision-making and closed-loop autonomy.
Compensation
- $228,000 - $285,000 (actual compensation will be determined based on experience, location, and other factors permitted by law).
Benefits
- Role Summary We are seeking a Staff Machine Learning Engineer interested in the development of end-to-end models that unify perception, prediction, and planning in a single system.
- Ideal candidates have experience with Supervised Learning, Reinforcement Learning, and/or LLMs.
- Rivian provides robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26.
- Coverage is effective on the first day of employment, and Rivian covers most of the premium
- This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information.
Company info
- Please note that we are currently not accepting applications from third party application services.
Equal opportunity
- Equal Opportunity Rivian is an
- equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.
This listing is sourced directly from Rivian's careers page and normalized into a canonical job model.