Tech Lead Manager, Machine Learning - Perception

About Rivian

Rivianis 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 Tech Lead Manager (TLM) to lead the evolution and scaling of our perception systems. You will guide a dedicated team in developing and deploying robust machine learning models that enable our vehicles to understand their environment. This role involves cross-functional collaboration, architecting solutions, and driving the technical roadmap to advance our perception technologies.

Responsibilities

As a member of our Autonomy organization, you will guide the strategy, architecture, and deployment of machine learning models for our vehicle's perception. These models support autonomous driving features and in-vehicle experiences by enabling environmental understanding. Your work will directly impact the core functionalities of our autonomous systems.
Key areas of impact include:
Technical Strategy & System Architecture: Define and drive the technical vision, architecture, and scaling roadmap for perception systems, ensuring they meet autonomous driving demands and champion new technologies
Perception Model Lifecycle Management: Lead the end-to-end development of scalable ML models for critical perception tasks (object detection, tracking, scene understanding, mapping), including MLOps, data pipelines, and optimization for robust onboard deployment
Team Leadership & Mentorship: Build, mentor, and lead a high-performing team of machine learning engineers, fostering a culture of innovation, technical excellence, and continuous improvement
Cross-Functional Collaboration & Integration: Partner effectively with teams across the autonomy stack (e.g., prediction, planning, simulation, hardware, ML infrastructure) to deliver seamlessly integrated and high-performing autonomous features

Qualifications

MS or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
Experience (typically 8+ years post-graduation) in machine learning, computer vision, or robotics, with significant work in perception for autonomous systems
Experience (typically 3+ years) in a technical leadership or management role, leading engineering teams on complex projects
Technical depth in machine learning, deep learning architectures (e.g., CNNs, Transformers), and computer vision algorithms
Experience developing and deploying perception algorithms (e.g., object detection, segmentation, tracking, SLAM, multi-sensor fusion) in real-world applications
Proficiency in Python and C++
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and MLOps tools/platforms
Communication, interpersonal, and collaboration skills for working in a dynamic, cross-functional environment

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 .
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Please note that we are currently not accepting applications from third party application services.

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