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 No Visa Sponsorship The Durability Attribute engineers predict and test the range of loads and stresses Rivian vehicles will experience over life and need to be durable for—a challenging prediction problem with many unknowns. With access to large-scale vehicle fleet data and software-defined vehicles that offer greater scope for control and autonomy, vehicle durability is at the forefront of data-driven engineering at Rivian ensuring the “Forever” in Rivian’s mission of Keeping the World Adventurous Forever. As a Durability Analytics Engineer, you will be part of the collaborative team of simulation, test, and data analytics engineers making Rivian vehicles adventurous yet durable for our customers. You will work with real-world, virtual, and vehicle test data, to identify, classify, and predict customer travel, driving, road surfaces, and other use cases, as well as undesirable events such as ground strikes or recovery events that impact loads on the vehicle and cause lifetime degradation. You will also develop and correlate a hybrid of data- and physics-based models to predict loads and vibrations at various suspension, body, and propulsion components to reduce the need for repeated complex-physics simulations and instrumented vehicle tests. Through your work, you will have the opportunity to improve process automation, efficiency, and standardization of vehicle durability target development. Responsibilities Fleet Data Analytics: Develop fleet data analyses mapping travel, driving, road infrastructure, and vehicle usage across the US and other markets. Build classification models to identify usage archetypes, usage frequency, and their correlations. Data-Driven Modeling and Standardization: , Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue damage, and vibration spectra from vehicle CAN data signals, wheel-force transducer data, or accelerometer data. Develop models to standardize vibration spectra at different vehicle locations across vehicle variants and platforms. Learn from simulation and test data to develop a library of regression models for variance in component loads and fatigue damage with variations in system design parameters and usage types. Process Optimization: Automate processes such as component block cycle development and accelerated duty cycle development from real-world duty cycle. Apply machine learning on past CAE results to develop ways to reduce the number of CAE test cases and runs. Qualifications Bachelor's degree in Mechanical Engineering, Aerospace Engineering, Computer Science or similar. A good understanding of vehicle physics and automotive engineering, is preferred. Passion for Rivian’s mission and commitment to fostering an inclusive, respectful, and collaborative workplace. 1-3 years experience in data analytics for automotive or related engineering applications, preferred. Experience with Python (Pandas, Numpy), PySpark, Matlab, and SQL applied to big datasets. Project or research experience with large time series datasets is desired. Demonstrated expertise with various machine learning techniques applied to automotive use data, test data, or simulation data. Experience in fatigue life estimation (e.g., Rainflow counting, Miner’s Rule) and statistical methods (e.g., Weibull analysis) Demonstrated experience in analytical writing (reports, white papers, publications) and clear-and-concise presentations, with attention to detail. Pay Disclosure The salary range for this role is $96,700 - $120,900 for California (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. 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). This job is not expected to be closed any sooner than 4/30/2026. 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. Fleet Data Analytics: Develop fleet data analyses mapping travel, driving, road infrastructure, and vehicle usage across the US and other markets. Build classification models to identify usage archetypes, usage frequency, and their correlations. Data-Driven Modeling and Standardization: , Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue damage, and vibration spectra from vehicle CAN data signals, wheel-force transducer data, or accelerometer data. Develop models to standardize vibration spectra at different vehicle locations across vehicle variants and platforms. Learn from simulation and test data to develop a library of regression models for variance in component loads and fatigue damage with variations in system design parameters and usage types. Process Optimization: Automate processes such as component block cycle development and accelerated duty cycle development from real-world duty cycle. Apply machine learning on past CAE results to develop ways to reduce the number of CAE test cases and runs. Bachelor's degree in Mechanical Engineering, Aerospace Engineering, Computer Science or similar. A good understanding of vehicle physics and automotive engineering, is preferred. Passion for Rivian’s mission and commitment to fostering an inclusive, respectful, and collaborative workplace. 1-3 years experience in data analytics for automotive or related engineering applications, preferred. Experience with Python (Pandas, Numpy), PySpark, Matlab, and SQL applied to big datasets. Project or research experience with large time series datasets is desired. Demonstrated expertise with various machine learning techniques applied to automotive use data, test data, or simulation data. Experience in fatigue life estimation (e.g., Rainflow counting, Miner’s Rule) and statistical methods (e.g., Weibull analysis) Demonstrated experience in analytical writing (reports, white papers, publications) and clear-and-concise presentations, with attention to detail.
