Define and drive execution of the technical roadmap and strategy for the E2E AI machinery, including training pipelines, optimization techniques, simulation and MLOps tooling.
Oversee the design, development, and testing of the E2E AI machinery and its interaction with data sources, model repositories, and development targets.
Collaborate closely with other functional tech leads (e.g. data engineering, infrastructure) to define and drive the overall architecture of the AI machinery ecosystem.
Guide the set-up of a development framework that enables fast evaluation and integration of emerging E2E AI solutions.
Guide the transition from research prototypes to production-ready solutions, ensuring performance optimization on automotive-grade hardware and scalability.
Leverage your prior industry experience in launching AI-based L2+ systems to implement best practices in system validation, testing (SIL/HIL), and continuous improvement.
Mentor and lead a high-caliber team of AI scientists and engineers, fostering a culture of innovation, collaboration, and technical excellence.
Requirements
Master's degree or Ph.D in Computer Science, Robotics, Electrical Engineering, AI, or a closely related field with a focus on autonomous systems
10+ years of experience in software development and system engineering for autonomous driving or ADAS applications
Proven industry experience in releasing AI-based L2+ systems, with a strong track record of successful product deployments
Deep knowledge of E2E AI stack solutions and training algorithms, including reinforcement learning, and imitation learning, as well as motion control and optimization techniques
Deep knowledge of AI frameworks such as TensorFlow and PyTorch
Deep knowledge in model optimization and embedded deployment of E2E AI stacks to embedded automotive hardware
Deep knowledge of cloud-based scalable training pipelines, MLOps, and CICD for training AI models with large-scale fleet datasets
Proven track record of leading the end-to-end development and successful deployment of complex AI-powered systems into production environments at scale
Experience with simulation tools and testing methodologies (SIL/HIL) for autonomous systems.
Proficiency in programming languages such as Python and C++.
Strong understanding of automotive safety standards (ISO 26262, ASIL) and regulatory requirements for ADAS.
Exceptional leadership and communication skills, with the ability to inspire and manage cross-functional teams.
Strategic thinker with strong problem-solving abilities and a passion for innovation in autonomous driving technology.
Equal Opportunity Employer, including disability / veterans
*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.
#LI-JM1
Benefits
Health insuranceDental insuranceVision insurance401(k)Flexible schedulePerformance bonusParental leave
Additional Information
As the Senior Principal Engineer, E2E AI Training Framework for Autonomous Driving Systems, you will spearhead the development and optimization of the machinery that efficiently trains, optimizes, tests, and releases various E2E AI-based products (e.g. parking, driving, interior sensing) for different trim levels (entry, mid and high) within our L2+ ADAS stack. You will be responsible for defining and driving the technological roadmap for the AI machinery, ensuring its scalability, reliability, and performance. The ideal candidate must have prior industry experience in releasing AI-based L2+ systems, with a proven track record of translating innovative research into production-grade solutions.
Boschgroup · Sunnyvale, CA