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 You will lead a team of six engineers who build the data acquisition, post-processing, analytics and dashboarding tools our validation engineers depend on to rapidly turn vehicle test data into clear, defensible results. Our mission is simple: find the pain points in the validation engineering workflow and remove them, whether that means a new tool, an extension to an existing one, better automation, or teaching engineers a better practice. This is a deliberately small, nimble team operating alongside much larger autonomy tooling and infrastructure organizations, and that shapes how we work. Our default is to leverage, customize and build on top of existing autonomy infrastructure and tooling whenever possible, instead of building parallel infrastructure of our own. You will bring the technical judgment behind those calls and will help drive the roadmap negotiations with peer organizations. You will also help bring AI-powered tools and agents into how this team and its customers work - across test infrastructure, data pipelines, triage, and process automation, enabling a six-person team to deliver the impact of a much larger one. Responsibilities Lead the team: Lead, coach and grow a team of six engineers, define the roadmap and prioritize the team’s workflow against limited capacity, stay hands on and drive cross-functional technical alignment and process improvements. Own the charter: Data acquisition, post-processing, analytics, data tools test automation, fleet software integration, and in-house data loggers where production logging falls short. Partner before building: Serve as the primary interface to the larger Autonomy software, platform, and infrastructure organizations. Extend what they already own, and build only the thin, high-leverage layer closest to the validation engineer whenever possible versus building from scratch. Develop dashboards: Automated reporting for active safety and automated driving feature test results, regulatory scoring, vehicle operator safety and behavior metrics and increase throughput on release metrics and validation KPIs. Lead CI/CD and quality: Run the pipelines and automated test framework for the team's repositories, report release health and stability, hold the quality gates and metric traceability that make results defensible and demonstrate the team is accelerating validation. Apply AI to the workflow: Identify and deploy AI tools and agents for test data and log triage, prioritize critical validation scenarios, report drafting, and implement new targeted evaluation methodologies, with judgment about where agentic automation fits and when other methods are better suited. Qualifications 5+ years in software engineering with a record of managing people and delivering cross-functional projects with a B.S. in Computer Science, Computer Engineering, Electrical Engineering, Robotics or related technical field. Strong hands-on Python experience building data tooling, pipelines, or analytics platforms for engineering or test organizations and demonstrated CI/CD and automated test framework experience (GitHub Actions, GitLab CI, or Jenkins, Docker, Pytest) in modern cloud services (AWS preferred). Practical experience with vehicle or robotics data: CAN (DBC, UDS / ISO 14229), automotive Ethernet, camera/radar/lidar logs, time synchronization, and formats such as MCAP, ROS, or MDF/MF4. Practical experience with LLMs and applied AI, including involvement with agent or automation systems and holding them to measurable accuracy metrics. Collaborative leader and clear communicator: Explain complex ideas simply, surface risks early, secure buy-in from stakeholders, develop meaningful dashboards and build a positive team culture. Bonus Qualifications ADAS or autonomous vehicle validation and physical vehicle testing, including Euro NCAP, US NCAP, IIHS, ISO, or UN protocols and ISO 26262 / ISO 21448. Data logging hardware and embedded logging software, or test fleet software lifecycle: builds, configuration management, OTA updates, and data offload at scale. Exposure to autonomy simulation, resimulation, and log-replay tooling, and how simulated coverage complements physical vehicle test results. Complex, safety-critical, or fast paced, high-uptime environments, and stacks such as Grafana, Streamlit, Databricks, Snowflake, or Airflow. Pay Disclosure The salary range for this role is $186,000 - $232,500 for Palo Alto, California 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. The successful candidate may be eligible for annual performance bonus and equity awards. 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. You can apply for this role through careers.rivian.com (or through internal-careers-rivian.icims.com if you are a current employee). There is no fixed deadline for this application; applications are accepted on an ongoing basis until the role is filled or the opening is no longer needed. 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. Lead the team: Lead, coach and grow a team of six engineers, define the roadmap and prioritize the team’s workflow against limited capacity, stay hands on and drive cross-functional technical alignment and process improvements. Own the charter: Data acquisition, post-processing, analytics, data tools test automation, fleet software integration, and in-house data loggers where production logging falls short. Partner before building: Serve as the primary interface to the larger Autonomy software, platform, and infrastructure organizations. Extend what they already own, and build only the thin, high-leverage layer closest to the validation engineer whenever possible versus building from scratch. Develop dashboards: Automated reporting for active safety and automated driving feature test results, regulatory scoring, vehicle operator safety and behavior metrics and increase throughput on release metrics and validation KPIs. Lead CI/CD and quality: Run the pipelines and automated test framework for the team's repositories, report release health and stability, hold the quality gates and metric traceability that make results defensible and demonstrate the team is accelerating validation. Apply AI to the workflow: Identify and deploy AI tools and agents for test data and log triage, prioritize critical validation scenarios, report drafting, and implement new targeted evaluation methodologies, with judgment about where agentic automation fits and when other methods are better suited. 5+ years in software engineering with a record of managing people and delivering cross-functional projects with a B.S. in Computer Science, Computer Engineering, Electrical Engineering, Robotics or related technical field. Strong hands-on Python experience building data tooling, pipelines, or analytics platforms for engineering or test organizations and demonstrated CI/CD and automated test framework experience (GitHub Actions, GitLab CI, or Jenkins, Docker, Pytest) in modern cloud services (AWS preferred). Practical experience with vehicle or robotics data: CAN (DBC, UDS / ISO 14229), automotive Ethernet, camera/radar/lidar logs, time synchronization, and formats such as MCAP, ROS, or MDF/MF4. Practical experience with LLMs and applied AI, including involvement with agent or automation systems and holding them to measurable accuracy metrics. Collaborative leader and clear communicator: Explain complex ideas simply, surface risks early, secure buy-in from stakeholders, develop meaningful dashboards and build a positive team culture. Bonus Qualifications ADAS or autonomous vehicle validation and physical vehicle testing, including Euro NCAP, US NCAP, IIHS, ISO, or UN protocols and ISO 26262 / ISO 21448. Data logging hardware and embedded logging software, or test fleet software lifecycle: builds, configuration management, OTA updates, and data offload at scale. Exposure to autonomy simulation, resimulation, and log-replay tooling, and how simulated coverage complements physical vehicle test results. Complex, safety-critical, or fast paced, high-uptime environments, and stacks such as Grafana, Streamlit, Databricks, Snowflake, or Airflow.
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