Sr. Autonomy Data Collection and Prototyping, Vehicle Build and Bring Up Engineer

📍 Job Overview

Job Title: Sr. Autonomy Data Collection and Prototyping, Vehicle Build and Bring Up Engineer

Company: Rivian

Location: Palo Alto, California, United States

Job Type: FULL_TIME

Category: Vehicle Operations & Engineering

Date Posted: 2026-05-19T20:26:00

Experience Level: Mid-Level (3+ years)

Remote Status: On-site

🚀 Role Summary

• This role is pivotal in bridging the gap between design engineering and the physical fleet of autonomy data collection vehicles, ensuring successful hardware and software integration.

• You will be instrumental in developing and implementing standardized processes and automation for vehicle build, upfitting, flashing, and testing cycles to scale operations efficiently.

• A key focus will be on ensuring the integrity and quality of collected data, which is crucial for downstream Data Science and Machine Learning consumers.

• This position requires a strong understanding of automotive diagnostic protocols, vehicle networking, and hands-on experience with scripting and automation to create robust, repeatable engineering solutions.

📝 Enhancement Note: This role sits at the intersection of engineering, operations, and data integrity. The emphasis on "building the process that builds the vehicle" indicates a strong focus on operational efficiency, scalability, and a proactive approach to problem-solving in a rapidly evolving prototyping environment. The title "Sr." suggests a need for independent problem-solving and potential mentorship.

📈 Primary Responsibilities

• Operational Handoff & Enablement: Lead the transition of complex build tasks from engineering to operator-led processes by creating clear work procedures, intuitive tooling, and comprehensive documentation.

• Workflow Optimization: Apply Industrial and Process Systems principles to identify and resolve bottlenecks in the "Build -> Upfit -> Flash -> Test" cycle, aiming to reduce cycle time while maintaining build integrity.

• Bring-Up Execution & Success: Own the end-to-end hardware and software bring-up for the data collection fleet, including firmware flashing, sensor calibration, and network verification (Ethernet/CAN) to ensure the autonomy data collection suite is mission-ready.

• Data Quality Assurance: Validate that all builds meet rigorous data-logging standards, ensuring correct sensor mounts, time-sync protocols, and logging configurations to prevent data corruption or bias.

• Hardware Upfit & Release Support: Lead the physical integration and modification of base vehicles into data collection platforms, overseeing the deployment of hardware releases across the prototype fleet.

• End-of-Line (EOL) & Quality Validation: Develop and implement EOL testing tools specific to the prototyping environment, authoring custom UDS RoutineControl sequences for automated electrical quality checks and service diagnostics.

• Cross-Functional Empowerment: Act as the technical lead for the shop floor, creating tools and documentation that enable technicians to perform high-level tasks with clarity and precision.

📝 Enhancement Note: The responsibilities highlight a blend of hands-on technical execution and strategic process development. The emphasis on "zero loss in quality" and "data integrity" points to a critical role in ensuring the reliability of data used for autonomous driving system development. The need to empower technicians suggests a focus on building scalable, operator-friendly processes.

🎓 Skills & Qualifications

Education:

Experience:

Required Skills:

• Industrial Systems & Build Orchestration: Strong background in Industrial or Systems Engineering with a passion for designing automated build sequences and Standard Operating Procedures (SOPs). Ability to architect the "Logical Flow" of a build, ensuring correct industrial sequence of hardware dependencies, software prerequisites, and validation steps.

• Diagnostic Protocols: High proficiency with ISO 14229 (UDS), DoIP (ISO 13400), and DoCAN (ISO 15765). Specific experience authoring Service RoutineControl sequences to automate hardware procedures and safety checks.

• Strategic Automation & AI Augmentation: Expert-level proficiency in Python or Bash to streamline and automate repetitive workflows. Ability to leverage AI-assisted engineering tools (LLMs/Agentic workflows) to accelerate robust, repeatable script development for high-reliability automation.

• EOL Test Frameworks: Hands-on experience with automotive test execution environments such as Vector CANoe/CANalyzer (CAPL), NI TestStand, or custom Python-based diagnostic frameworks (e.g., udsoncan, python-can).

• Systems & Networking: Strong knowledge of vehicle network architecture (Automotive Ethernet, CAN/CAN-FD, TCP/IP, UDP) and ability to perform deep-dive debugging on high-speed data links.

• Software Deployment: Experience with Linux-based system administration, shell scripting, and Hardware-in-the-Loop (HiL) validation to ensure software stack integrity.

• Hands-On Mentality: Comfort with both terminal operations and physical tools (multimeter, oscilloscope, crimping tool); passion for on-the-ground problem-solving and hardware upfits.

Preferred Skills:

• Experience with AI-assisted engineering tools for script development.

• Familiarity with other automotive communication protocols.

• Experience in a fast-paced, startup-like environment.

📝 Enhancement Note: The emphasis on "AI-assisted engineering tools" and "Agentic workflows" indicates a forward-thinking approach to development and automation, suggesting candidates who are adaptable and eager to leverage emerging technologies will be highly valued. The explicit mention of "Golden Build" processes highlights the importance of creating highly reliable and reproducible procedures.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Process Optimization Case Studies: Showcase examples of how you've analyzed and improved complex build, integration, or testing processes, detailing the methodology used and quantifiable results achieved.

• Automation Script Examples: Provide code snippets or descriptions of Python/Bash scripts developed to automate diagnostic routines, data collection, or build verification tasks. Highlight efficiency gains and error reduction.

• Diagnostic Workflow Design: Include examples of diagnostic sequences or EOL test frameworks you've designed or implemented, demonstrating proficiency with UDS, DoIP, and automotive networking.

• Data Integrity Solutions: Illustrate instances where you've implemented measures to ensure data quality and integrity for downstream consumers, such as sensor calibration verification or logging configuration validation.

Process Documentation:

• Demonstrate experience in creating clear, concise, and actionable Standard Operating Procedures (SOPs) for complex technical tasks.

• Showcase ability to develop intuitive tooling and documentation that empowers less experienced operators to execute high-level engineering tasks.

• Evidence of creating logical build flows that account for hardware dependencies, software prerequisites, and validation steps.

📝 Enhancement Note: For this role, a portfolio should strongly emphasize practical application of engineering principles to operational challenges. Candidates should be prepared to walk through their contributions to process improvement, automation development, and the creation of reliable systems that enable scalable operations, particularly in a prototyping context.

💵 Compensation & Benefits

Salary Range: $162,800 - $203,500 USD per year (for San Francisco Bay Area applicants)

Benefits:

• Paid Vacation

• Paid Sick Leave

• Medical Insurance

• Dental Insurance

• Vision Insurance

• Life Insurance

• Short-term Disability Insurance

• Long-term Disability Insurance

• Rivian's 401(k) Plan (eligibility requirements apply)

Working Hours:

• Typically 40 hours per week, with potential for overtime given the hands-on nature of prototyping and vehicle bring-up.

📝 Enhancement Note: The salary range provided is specific to the San Francisco Bay Area. Candidates in other locations may see variations. The comprehensive benefits package is standard for full-time roles at a company of Rivian's size and industry presence, offering robust support for employees and their families.

🎯 Team & Company Context

🏢 Company Culture

Industry: Automotive Manufacturing (Electric Vehicles), Technology, Autonomous Driving

Company Size: Large (1,000-5,000+ employees, based on general knowledge of Rivian's scale)

Founded: 2019 (Rivian was officially founded in 2009, but the brand and public presence ramped up significantly later; the provided JSON often has newer dates for "founded" in certain contexts, but the industry standard is 2009 for the company's origin. For this enhancement, we will use the more commonly known origin.)

Team Structure:

• This role is part of the Autonomy Data Collection and Prototyping team, which likely operates within a larger Engineering or Vehicle Operations division.

• The team collaborates closely with core design engineering teams, Data Science, Machine Learning, and potentially manufacturing operations.

Methodology:

• Data-Driven Development: Heavy reliance on data integrity and analysis from prototype vehicles to inform ML models and system improvements.

• Process Engineering: Application of industrial and systems engineering principles to optimize workflows, reduce cycle times, and ensure repeatability.

• Agile Prototyping: Rapid iteration and deployment of hardware and software in a dynamic prototyping environment.

• Cross-Functional Collaboration: Strong emphasis on working with diverse teams to achieve complex engineering and operational goals.

Company Website: https://www.rivian.com/

📝 Enhancement Note: Rivian's culture is often described as innovative, fast-paced, and mission-driven, with a strong emphasis on sustainability and adventure. For operations roles, this translates to a need for adaptability, problem-solving, and a proactive approach to building and refining processes in a cutting-edge field.

📈 Career & Growth Analysis

Operations Career Level: Senior Engineer. This level implies a significant degree of autonomy, responsibility for complex projects, and the ability to influence process and technical direction within the team. It suggests a need for strong technical expertise combined with process development skills.

Reporting Structure: The role will report to a manager responsible for vehicle operations or prototyping for the autonomy division. There will be close collaboration with various engineering disciplines, including software, hardware, and data science, requiring effective communication and stakeholder management.

Operations Impact: This role is critical for enabling the development of Rivian's autonomous driving capabilities. By ensuring high-quality data collection and reliable vehicle platforms, the engineer directly impacts the speed and effectiveness of ML model training and validation, ultimately influencing the launch and refinement of autonomous features. Success here means more reliable data, faster iteration cycles, and accelerated progress towards advanced driver-assistance systems and full autonomy.

Growth Opportunities:

• Technical Specialization: Deepen expertise in automotive diagnostics, vehicle networking, or AI-assisted automation within the autonomy space.

• Process Leadership: Transition into roles focused on scaling manufacturing or prototyping operations, leading process improvement initiatives, or managing larger teams.

• Cross-Functional Mobility: Opportunities to move into roles within broader vehicle engineering, software development, or operations management.

• Mentorship: Potential to mentor junior engineers and technicians, guiding them in build processes, troubleshooting, and best practices.

📝 Enhancement Note: The "Sr." title suggests that candidates are expected to not only execute but also to innovate and lead in process development. The growth opportunities highlight a clear path for individuals who excel in optimizing operational efficiency and technical reliability within the complex domain of autonomous vehicle development.

🌐 Work Environment

Office Type: On-site, likely a combination of office space and a hands-on prototyping facility or vehicle build shop.

Office Location(s): Palo Alto, California, with the prototyping and build activities occurring at a dedicated facility, potentially near other Rivian engineering hubs.

Workspace Context:

• Collaborative Environment: The role requires close collaboration with engineers, technicians, and potentially data scientists. Expect a dynamic workspace with regular team interactions.

• Tools & Technology: Access to advanced diagnostic equipment, lab tools, vehicle lifts, networking hardware, and robust computing resources for scripting and simulation.

• Hands-On Focus: A significant portion of the work involves direct interaction with vehicles and hardware, requiring a willingness to be on the shop floor ("Gemba").

Work Schedule:

• Standard 40-hour work week is typical, but flexibility may be required to accommodate vehicle bring-up schedules, hardware deployments, and critical issue resolution, potentially involving non-standard hours or weekend work during intense project phases.

📝 Enhancement Note: This role demands a candidate who thrives in both technical problem-solving environments and collaborative team settings. The physical nature of the work combined with the intellectual rigor of process engineering and automation is a key characteristic of this position.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or Recruiter call to assess basic qualifications, interest, and cultural fit.

• Technical Phone Screen: Interview with an engineering lead or senior team member to dive deeper into technical skills, experience with automotive protocols, scripting, and process development.

• On-site/Virtual Loop: This typically involves multiple interviews covering:

  • Deep Technical Dive: Detailed discussion on diagnostic protocols, networking, scripting, and EOL test development. Expect scenario-based questions and problem-solving challenges.
  • Process & Systems Thinking: Assessment of your approach to workflow optimization, SOP creation, and scaling operational processes. Questions may involve hypothetical build scenarios.
  • Portfolio Review: Presentation of your past work, focusing on process improvements, automation projects, and contributions to data integrity or vehicle bring-up. Be prepared to discuss your role, methodology, and impact.
  • Behavioral & Cultural Fit: Questions to gauge your collaboration style, problem-solving approach under pressure, and alignment with Rivian's values.
  • Hiring Manager Interview: Final discussion on role expectations, team dynamics, and career aspirations.

Portfolio Review Tips:

• Focus on Impact: For each project, clearly articulate the problem, your specific contribution, the methodology used (e.g., process mapping, automation scripting), and the quantifiable results (e.g., time saved, error reduction, data quality improvement).

• Showcase Automation: Highlight your Python/Bash scripts, and be ready to discuss the logic, efficiency gains, and any AI assistance used in their development.

• Demonstrate Protocol Proficiency: Use examples of UDS, DoIP, or CAN/CAN-FD implementations, especially in diagnostic or EOL testing contexts.

• Process Engineering Clarity: Present SOPs or workflow diagrams that are clear, logical, and easy for a non-expert to understand. Emphasize how your processes ensure data integrity.

• Prepare for Questions: Anticipate questions about your problem-solving approach, how you handle ambiguity, and how you collaborate with different teams.

Challenge Preparation:

• Diagnostic Scenario: Be ready to walk through troubleshooting a complex vehicle network issue or a failed EOL test.

• Process Improvement Task: You might be asked to outline how you would improve a hypothetical vehicle build or data collection process.

• Scripting/Automation Task: A small coding challenge or a discussion about how you would automate a specific task might be included.

📝 Enhancement Note: Candidates should prepare to demonstrate not only their technical acumen but also their ability to translate complex engineering requirements into scalable, repeatable operational processes. The portfolio review is a critical component, so showcasing tangible examples of process improvement and automation is key.

🛠 Tools & Technology Stack

Primary Tools:

• Diagnostic Protocols: ISO 14229 (UDS), ISO 13400 (DoIP), ISO 15765 (DoCAN).

• Automation Scripting: Python, Bash.

• Automotive Test Frameworks: Vector CANoe/CANalyzer (CAPL), NI TestStand, custom Python diagnostic frameworks (e.g., udsoncan, python-can).

• Vehicle Networking: Automotive Ethernet, CAN/CAN-FD, TCP/IP, UDP.

• Operating Systems: Linux (for system administration and scripting).

• Hardware & Tools: Multimeter, oscilloscope, crimping tools, diagnostic hardware interfaces.

Analytics & Reporting:

CRM & Automation:

• Not directly applicable to this role's core technical functions, but awareness of how vehicle data is managed within larger systems could be a plus.

📝 Enhancement Note: The technology stack is heavily focused on automotive diagnostics, embedded systems, and automation scripting. Proficiency in Python and specific automotive protocols like UDS and DoIP is non-negotiable. Experience with industry-standard tools like Vector CANoe is highly desirable.

👥 Team Culture & Values

Operations Values:

• Innovation & Curiosity: A drive to explore new solutions and challenge existing norms, especially in the rapidly evolving field of autonomous driving.

• Data Integrity & Quality: A commitment to ensuring the highest standards of data accuracy, which is foundational for ML development.

• Efficiency & Scalability: A focus on building processes that are not only effective but also scalable to meet the demands of a growing fleet and development cycles.

• Collaboration & Empowerment: A belief in teamwork and empowering technicians and operators to perform complex tasks with clear guidance and support.

• Hands-On Problem Solving: A culture that values direct engagement with challenges, whether in code or on the shop floor.

Collaboration Style:

• Cross-Functional Integration: Expect to work closely with diverse teams, requiring strong communication skills to bridge gaps between engineering and operations.

• Process Improvement Culture: An environment where feedback is encouraged, and continuous improvement of workflows is a shared goal.

• Knowledge Sharing: A willingness to share expertise, document processes, and help upskill team members.

📝 Enhancement Note: Rivian's culture emphasizes a blend of cutting-edge technology development with a practical, hands-on approach. For this role, it means being comfortable with both sophisticated diagnostic tools and the tangible work of building and integrating hardware.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Prototyping Pace: Working in a fast-paced environment with evolving requirements and tight deadlines for vehicle deployments.

• First-of-Kind Issues: Troubleshooting novel hardware and software integration problems that may not have pre-existing solutions.

• Data Integrity at Scale: Ensuring consistent data quality across a growing fleet of prototype vehicles under varying conditions.

• Bridging Engineering & Operations: Effectively translating complex engineering specifications into understandable and executable processes for operators.

Learning & Development Opportunities:

• Deep Dive into Autonomy Stacks: Gain in-depth knowledge of the hardware and software components that form Rivian's autonomous driving systems.

• Advanced Diagnostic Techniques: Master complex vehicle communication protocols and advanced troubleshooting methodologies.

• AI-Assisted Development: Develop expertise in leveraging AI tools for faster script creation and process automation.

• Process Engineering Leadership: Opportunities to lead initiatives in workflow optimization and operational scaling within a high-growth automotive company.

📝 Enhancement Note: This role presents significant opportunities for growth in a cutting-edge field. The challenges are inherent to pioneering new technologies and processes, offering a steep learning curve and the chance to make a tangible impact on the future of autonomous vehicles.

💡 Interview Preparation

Strategy Questions:

• Process Improvement: "Describe a time you improved a complex manufacturing or prototyping process. What was your methodology, and what were the quantifiable results?"

• Automation Design: "How would you automate the process of flashing firmware and verifying sensor calibration on a fleet of 50 vehicles? What scripting language would you use, and what are the key considerations for reliability?"

• Diagnostic Troubleshooting: "A vehicle on the data collection fleet is intermittently losing connection to its primary sensor array over Automotive Ethernet. How would you approach diagnosing this issue?"

• Data Integrity: "What steps would you take to ensure the time-synchronization accuracy of all sensors on a data collection vehicle, and why is this critical for ML model training?"

Company & Culture Questions:

• "What interests you about Rivian's mission and its approach to electric adventure vehicles?"

• "How do you approach working with technicians or operators who may have different technical backgrounds than your own?"

Portfolio Presentation Strategy:

• Structure: For each project, use a STAR (Situation, Task, Action, Result) or similar format. Clearly define the problem, your role, the steps you took, and the outcome.

• Quantify Impact: Use metrics whenever possible (e.g., reduced cycle time by X%, decreased error rate by Y%, increased data collection uptime by Z%).

• Showcase Code: Be prepared to share or describe your automation scripts, highlighting key logic and efficiency gains.

• Process Visuals: Use diagrams, flowcharts, or SOP examples to illustrate your process design skills.

• Focus on Collaboration: Explain how you worked with others to achieve project goals.

📝 Enhancement Note: Interview preparation should heavily focus on demonstrating practical problem-solving skills, a strong grasp of automotive systems and protocols, and a clear ability to translate technical requirements into robust operational processes. Candidates should be ready to articulate their contributions with specific examples and measurable outcomes.

📌 Application Steps

To apply for this operations position:

• Submit your application through the Rivian Careers portal using the provided link.

• Tailor Your Resume: Ensure your resume highlights experience with automotive diagnostics (UDS, DoIP), scripting (Python, Bash), vehicle networking, process optimization, and any experience in prototyping or manufacturing environments. Use keywords from the job description.

• Prepare Your Portfolio: Curate examples of process improvements, automation scripts, diagnostic workflows, and data integrity initiatives. Be ready to present these clearly and concisely, focusing on quantifiable results.

• Research Rivian: Understand the company's mission, products, and recent developments, particularly concerning their approach to autonomous technology and vehicle development.

• Practice Interview Questions: Prepare for technical, behavioral, and situational questions, focusing on your ability to solve complex problems and optimize operational processes.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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