What you'd actually do

Design and implementation of learning-based prediction and planning systems, including end-to-end models for real-world driving.

Develop hybrid planning architectures that combine transformer-based prediction/planning with classical methods such as MPC and graph-based planning.

Drive end-to-end ownership across data collection, dataset curation, model training, optimization, deployment, and closed-loop evaluation.

Define and enforce safety and feasibility strategies for trajectory generation, including fallback behaviors and runtime safeguards.

Partner with Perception and Systems teams to integrate planning models into production-like stacks and ensure robust interface contracts.

Skills

Required

Master’s or PhD in Robotics, Control Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
Strong background in autonomous driving prediction and planning, with hands-on experience in both research and deployment.
Deep knowledge of trajectory prediction and planning methods, including transformer-based architectures and sequence modeling.
Strong fundamentals in control and robotics, including MPC, graph search, state estimation, and vehicle behavior modeling.
Proficiency in Python and C++ for production-quality software development.
Hands-on experience with PyTorch and deployment acceleration frameworks (for example TensorRT/ONNX) in real-time systems.
Experience with ROS/Autoware-style robotics integration and simulation-based development workflows.
Strong understanding of open-loop vs closed-loop evaluation, KPI design, failure analysis, and safety-driven model validation.
Demonstrated technical leadership, cross-functional collaboration, and ability to deliver under tight product timelines.
Excellent communication and problem-solving skills in fast-paced, multidisciplinary environments.

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 Senior Engineer in Prediction, Planning, and Controls to join our Autonomy team in London. This role is focused on developing and deploying learning-based and hybrid planning systems for production-oriented autonomous driving. The ideal candidate combines strong robotics fundamentals with modern ML expertise and can lead end-to-end delivery from data and model development to in-vehicle validation. Responsibilities Design and implementation of learning-based prediction and planning systems, including end-to-end models for real-world driving. Develop hybrid planning architectures that combine transformer-based prediction/planning with classical methods such as MPC and graph-based planning. Drive end-to-end ownership across data collection, dataset curation, model training, optimization, deployment, and closed-loop evaluation. Define and enforce safety and feasibility strategies for trajectory generation, including fallback behaviors and runtime safeguards. Partner with Perception and Systems teams to integrate planning models into production-like stacks and ensure robust interface contracts. Improve real-time inference performance for in-vehicle deployment using model optimization techniques and toolchains such as TensorRT. Build and scale evaluation pipelines that connect offline metrics with closed-loop behavior in simulation and on-road testing. Lead scenario-based validation for rare and safety-critical edge cases, and use results to drive model and system improvements. Mentor peers and contribute technical leadership across planning and prediction initiatives. Qualifications Master’s or PhD in Robotics, Control Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field. Strong background in autonomous driving prediction and planning, with hands-on experience in both research and deployment. Deep knowledge of trajectory prediction and planning methods, including transformer-based architectures and sequence modeling. Strong fundamentals in control and robotics, including MPC, graph search, state estimation, and vehicle behavior modeling. Proficiency in Python and C++ for production-quality software development. Hands-on experience with PyTorch and deployment acceleration frameworks (for example TensorRT/ONNX) in real-time systems. Experience with ROS/Autoware-style robotics integration and simulation-based development workflows. Strong understanding of open-loop vs closed-loop evaluation, KPI design, failure analysis, and safety-driven model validation. Demonstrated technical leadership, cross-functional collaboration, and ability to deliver under tight product timelines. Excellent communication and problem-solving skills in fast-paced, multidisciplinary environments. 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.

Senior Machine Learning / AI Engineer

What you'd actually do

Skills

Required

What the JD emphasized

Other signals