Sr. Process Engineer, R1 Body AIML

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 whats 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 Rivian is seeking an innovative engineer who combines expertise in AI/ML with a passion for quality and manufacturing excellence in the Body Assembly area. This role is crucial in driving our digital transformation initiatives through the development and implementation of AI-powered solutions. The position offers the opportunity to revolutionize our manufacturing processes using cutting-edge AI technologies while working closely with quality teams to enhance systems tools and customer relationships. The opening is located at our Normal IL facility and reports directly to the Process Engineering Manager. Shift Flexibility is required for these engineers Responsibilities Process Optimization & Modeling: Apply fundamental process engineering principles and advanced statistical methods including ML/AI algorithms to analyze manufacturing data (e.g. End of line test data sensor data press data LVDT data historical trends operational logs). Develop and implement predictive models for key performance indicators (KPIs) such as yield throughput and equipment downtime. Data Strategy & Management: Collaborate with IT and operations teams to establish data pipelines ensuring data quality accessibility and integrity for ML model training and deployment. Utilize data collected by Rivians MES database system for model training. Model Development & Deployment: Design train validate and deploy robust ML models (e.g. classification regression time-series forecasting) for real-time process control anomaly detection predictive maintenance and quality prediction. Document model methodologies deployment procedures and process changes. Present complex findings and recommendations clearly to technical and non-technical stakeholders. Qualifications Education: Bachelors degree in Electrical engineering Computer Engineering Computer Science Data Science Statistics or other related engineering degree. 3-5 years of experience in a process or manufacturing engineering role specifically applying Machine Learning data science or advanced statistical modeling in an industrial setting. Technical Skills: Programming: High proficiency in Python or R Data & Databases: Strong SQL skills and experience working with time-series databases (e.g. OSIsoft PI InfluxDB) or cloud data platforms (e.g. Azure AWS GCP) high proficiency in Hex/Databricks for custom dashboards designing. Statistical/ML Proficiency: Expertise in statistical analysis multivariate analysis regression and various ML algorithms. Experience in using 2D & 3D Modeling tools (AutoCAD CATIA/ENOVIA) Experience and/or Knowledge in DOE Geometric Dimensioning & Tolerance Torque Tooling Error Proofing and PFMEA Experience and/or certification in Six Sigma DMAIC (optional) Lean Assembly Principles Time Studies using MTM or MODAPTS Strong verbal and written communication skills Demonstrated strong analytical and problem-solving skills Ability to work in teams and collaborate effectively with people in different functions Ability to take the initiative and drive for results Strong time management skills that enable on-time project delivery Pay Disclosure The salary range for this role is $98500-$123100 for Illinois 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 employees 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 Rivians 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 . You can apply for this role through (or through if you are a current employee). This job is not expected to be closed any sooner than November 16th2026. 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 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) Rivians 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.
Process Optimization & Modeling: Apply fundamental process engineering principles and advanced statistical methods including ML/AI algorithms to analyze manufacturing data (e.g. End of line test data sensor data press data LVDT data historical trends operational logs). Develop and implement predictive models for key performance indicators (KPIs) such as yield throughput and equipment downtime. Data Strategy & Management: Collaborate with IT and operations teams to establish data pipelines ensuring data quality accessibility and integrity for ML model training and deployment. Utilize data collected by Rivians MES database system for model training. Model Development & Deployment: Design train validate and deploy robust ML models (e.g. classification regression time-series forecasting) for real-time process control anomaly detection predictive maintenance and quality prediction. Document model methodologies deployment procedures and process changes. Present complex findings and recommendations clearly to technical and non-technical stakeholders.
Education: Bachelors degree in Electrical engineering Computer Engineering Computer Science Data Science Statistics or other related engineering degree. 3-5 years of experience in a process or manufacturing engineering role specifically applying Machine Learning data science or advanced statistical modeling in an industrial setting. Technical Skills: Programming: High proficiency in Python or R Data & Databases: Strong SQL skills and experience working with time-series databases (e.g. OSIsoft PI InfluxDB) or cloud data platforms (e.g. Azure AWS GCP) high proficiency in Hex/Databricks for custom dashboards designing. Statistical/ML Proficiency: Expertise in statistical analysis multivariate analysis regression and various ML algorithms. Experience in using 2D & 3D Modeling tools (AutoCAD CATIA/ENOVIA) Experience and/or Knowledge in DOE Geometric Dimensioning & Tolerance Torque Tooling Error Proofing and PFMEA Experience and/or certification in Six Sigma DMAIC (optional) Lean Assembly Principles Time Studies using MTM or MODAPTS Strong verbal and written communication skills Demonstrated strong analytical and problem-solving skills Ability to work in teams and collaborate effectively with people in different functions Ability to take the initiative and drive for results Strong time management skills that enable on-time project delivery