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 a highly motivated Controls & Active Safety Engineer to join our team, specializing in active safety feature development for autonomous and semi-autonomous vehicles. This candidate will design, implement, and validate safety-critical systems, with a strong emphasis on integrating controls, machine learning, and AI-based algorithms to advance detection, prediction, and decision-making capabilities. Proficient in C++, Python, and related technologies, they bring hands-on experience in ML/AI model development, data analysis, and real-time system optimization. Their collaborative approach and familiarity with automotive safety standards make them well-equipped to drive innovation and reliability in advanced vehicle safety applications within the Controls team. Responsibilities Design, develop, and validate active safety features such as collision avoidance, lane keeping, and emergency braking for autonomous vehicles. Collaborate with cross-functional teams to integrate AI-based algorithms into safety-critical systems, leveraging data-driven approaches to enhance detection, prediction, and decision-making capabilities. Work closely with data engineering and autolabeling teams to ensure high-quality training and validation datasets for ML/AI models. Collaborate with data engineering and autolabeling teams to ensure high-quality, accurately labeled datasets that support the development and validation of ML/AI-driven controls and active safety features, enabling robust reasoning and decision-making capabilities in real-world scenarios. Analyze sensor data and vehicle dynamics to improve the performance of ML/AI models used in active safety applications. Develop and maintain simulation and testing frameworks to ensure robust performance in real-world scenarios. Troubleshoot, debug, and optimize safety features and ML/AI algorithms for reliability and performance across diverse driving environments. Qualifications Bachelor’s/Master’s/PhD degree in Engineering, Computer Science, Data Science, or a related field. Direct industry experience as a software engineer in robotics, autonomous vehicles, or other real-time, safety-critical environments. Strong proficiency in modern C++, Python, and experience with ML frameworks, along with experience applying large-scale software engineering best practices. Strong background in machine learning, AI, and robotics, with hands-on experience developing and deploying learning-based algorithms. Experience designing, deploying, and maintaining systems with core AWS services (such as S3, EC2, Lambda), and a solid understanding of cloud-native architecture. Familiarity with autonomous systems development, including perception, planning, or control, or related fields such as robotics, simulation, or verification and validation. Demonstrated ability to systematically debug and identify root causes of issues. Strong analytical and problem-solving skills, with attention to detail Familiarity with automotive safety standards and real-time system development. Excellent problem-solving and communication skills. Pay Disclosure The salary range for this role is $130,600.00 - $163,300.00 for 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). This job is not expected to be closed any sooner than February 25, 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 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. Please note that we are currently not accepting applications from third party application services.
Software Engineer Ii, Controls & Active Safety Engineer, Autonomy
Software Engineer II, Controls & Active Safety Engineer at Rivian, focusing on developing and validating active safety features for autonomous vehicles. This role involves integrating AI/ML algorithms into safety-critical systems, analyzing sensor data, and optimizing ML models for real-time performance. Requires strong C++, Python, and ML framework experience, with a background in robotics or autonomous systems.
What you'd actually do
- Design, develop, and validate active safety features such as collision avoidance, lane keeping, and emergency braking for autonomous vehicles.
- Collaborate with cross-functional teams to integrate AI-based algorithms into safety-critical systems, leveraging data-driven approaches to enhance detection, prediction, and decision-making capabilities.
- Work closely with data engineering and autolabeling teams to ensure high-quality training and validation datasets for ML/AI models.
- Collaborate with data engineering and autolabeling teams to ensure high-quality, accurately labeled datasets that support the development and validation of ML/AI-driven controls and active safety features, enabling robust reasoning and decision-making capabilities in real-world scenarios.
- Analyze sensor data and vehicle dynamics to improve the performance of ML/AI models used in active safety applications.
Skills
Required
- Bachelor’s/Master’s/PhD degree in Engineering, Computer Science, Data Science, or a related field
- Direct industry experience as a software engineer in robotics, autonomous vehicles, or other real-time, safety-critical environments
- Strong proficiency in modern C++, Python
- experience with ML frameworks
- experience applying large-scale software engineering best practices
- Strong background in machine learning, AI, and robotics
- hands-on experience developing and deploying learning-based algorithms
- Experience designing, deploying, and maintaining systems with core AWS services
- solid understanding of cloud-native architecture
- Familiarity with autonomous systems development, including perception, planning, or control, or related fields such as robotics, simulation, or verification and validation
- Demonstrated ability to systematically debug and identify root causes of issues
- Strong analytical and problem-solving skills
- attention to detail
- Familiarity with automotive safety standards
- real-time system development
- Excellent problem-solving and communication skills
What the JD emphasized
- safety-critical systems
- real-time
- ML/AI model development
- ML/AI algorithms
- automotive safety standards
- real-time system development
Other signals
- integrating AI-based algorithms into safety-critical systems
- developing and deploying learning-based algorithms
- real-time system optimization