Rivian
From Rivian's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done.
About Rivian Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. 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. Role Summary We are seeking an expert AV data strategist to architect the data engine and collection frameworks that power our next-generation perception and end-to-end autonomous driving models. Sitting at the intersection of systems engineering, machine learning infrastructure, and vehicle operations, you will design the system-level strategies for how we identify, capture, and utilize fleet data. Your work will ensure our models are trained and evaluated on highly relevant, diverse, and safe datasets, prioritizing high-quality continuous driving sequences while balancing strict vehicle edge constraints. Responsibilities Define and document comprehensive data requirements to support diverse training, development and evaluation use cases across the autonomy stack. Build and manage a decision-making framework with cross-functional stakeholders. Use this framework to determine data availability, identify gaps between required vs. available data, and prioritize collection efforts of desired driving behaviors, trajectory profiles or scenes. Driven by the gap analysis, devise strategies to capture required data from the fleet. Ensure the data meets required recall, precision and diversity requirements while operating within the constraints of on-vehicle data logging, privacy, and upload bandwidth. Collaborate with Autonomy ML teams to systematically identify model failure modes and define requirements for targeted data mining campaigns to resolve them. Define strategies and standards for data slicing tailored to training, development and evaluation of autonomy perception, planning and end-to-end models. Coordinate the deployment of tagging with data and cloud teams. Curate diverse, high fidelity datasets that capture targeted ODD scenes and human driving demonstrations, systematically filtering out sub-optimal behaviors. Review and provide strategic inputs on perception taxonomy requirements—such as defining object and scene classifications, attributes etc.—to meet the demands of different autonomy features on the target vehicle platform or target customer market. Define system metrics to evaluate the health, diversity, and potential bias of driving datasets, ensuring they accurately represent our Operational Design Domain (ODD) and comply with safety and verification standards. Qualifications Advanced degree (Master’s or Ph.D.) in Systems Engineering, Computer Science, Robotics, Machine Learning, Data science or a related technical field . 10+ years (Bachelor’s)/8+ years (Master’s) of experience in systems engineering, data strategy, or MLOps, preferably carrying out listed responsibilities in the Autonomous driving or robotics industry. Understanding of autonomy data requirements for perception models, end-to-end models, imitation learning, and sensor-to-trajectory model training lifecycles. Demonstrated ability to build technical frameworks from the ground up and drive consensus among teams such as ML software, data and cloud infrastructure and vehicle operations. Medium to Strong programming skills in Python and one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Knowledge of privacy engineering, data privacy, security risks, and controls Excellent team player with strong communication and presentation skills. Pay Disclosure The salary range for this role is $265,000-$331,300 for San Francisco Bay Area based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs. We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian’s 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com. Equal Opportunity Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com. Candidate Data Privacy and Technology Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law. Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services. Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions. How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role. AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate. Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way. Interview Integrity & AI Policy Our interview process is designed to evaluate your personal technical foundation, real-time problem-solving logic, and structured capabilities. Therefore, the use of assistive generative AI tools to formulate or deliver your solutions during live interview sessions is not permitted. We care most about how you think — how you make sense of unclear requirements, weigh trade-offs, and explain why you chose one approach over another. We value your unique human perspective, your authenticity, and the journey it takes to reach a solution. Please note that we are currently not accepting applications from third party application services. Define and document comprehensive data requirements to support diverse training, development and evaluation use cases across the autonomy stack. Build and manage a decision-making framework with cross-functional stakeholders. Use this framework to determine data availability, identify gaps between required vs. available data, and prioritize collection efforts of desired driving behaviors, trajectory profiles or scenes. Driven by the gap analysis, devise strategies to capture required data from the fleet. Ensure the data meets required recall, precision and diversity requirements while operating within the constraints of on-vehicle data logging, privacy, and upload bandwidth. Collaborate with Autonomy ML teams to systematically identify model failure modes and define requirements for targeted data mining campaigns to resolve them. Define strategies and standards for data slicing tailored to training, development and evaluation of autonomy perception, planning and end-to-end models. Coordinate the deployment of tagging with data and cloud teams. Curate diverse, high fidelity datasets that capture targeted ODD scenes and human driving demonstrations, systematically filtering out sub-optimal behaviors. Review and provide strategic inputs on perception taxonomy requirements—such as defining object and scene classifications, attributes etc.—to meet the demands of different autonomy features on the target vehicle platform or target customer market. Define system metrics to evaluate the health, diversity, and potential bias of driving datasets, ensuring they accurately represent our Operational Design Domain (ODD) and comply with safety and verification standards. Advanced degree (Master’s or Ph.D.) in Systems Engineering, Computer Science, Robotics, Machine Learning, Data science or a related technical field . 10+ years (Bachelor’s)/8+ years (Master’s) of experience in systems engineering, data strategy, or MLOps, preferably carrying out listed responsibilities in the Autonomous driving or robotics industry. Understanding of autonomy data requirements for perception models, end-to-end models, imitation learning, and sensor-to-trajectory model training lifecycles. Demonstrated ability to build technical frameworks from the ground up and drive consensus among teams such as ML software, data and cloud infrastructure and vehicle operations. Medium to Strong programming skills in Python and one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Knowledge of privacy engineering, data privacy, security risks, and controls Excellent team player with strong communication and presentation skills.
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