Senior Principal Engineer- End-to-End AI Training Framework at Bosch Group

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

19 May, 26

Salary

320000.0

Posted On

18 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Training Framework, Autonomous Driving, Product Engineering, Technical Roadmap, Training Pipelines, Optimization Techniques, MLOps Tooling, System Validation, Reinforcement Learning, Imitation Learning, TensorFlow, PyTorch, Embedded Deployment, Cloud-based Training, CICD, Leadership

Industry

Software Development

Description

Company Description “Invented for Life” drives us at Bosch and our vision of future mobility. Autonomous vehicles will change the way we move and at Bosch we are working on making this future a reality. We are now growing our team to solve some of the hardest automated driving problems, and are looking for experts for product engineering of AI-based Autonomous Driving systems. Job Description 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. Key Responsibilities 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. Qualifications Basic Qualifications: 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 Preferred Qualifications: 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. Additional Information The U.S. base salary range for this full-time position is $240,000 - $320,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. This range does not include annual bonus percentage nor any other monetary considerations for the total compensation package. Your Recruiter can share more details about the specific salary range for this position during the interview process. In addition to your base salary, Bosch offers a comprehensive benefits package that includes health, dental, and vision plans; health savings accounts (HSA); flexible spending accounts; 401(K) retirement plan with an attractive employer match; wellness programs; life insurance; long term disability insurance; paid time off; parental leave. Pay ranges included in the postings, when included, generally reflect base salary; certain positions may include bonus, or additional benefits. 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 Legal Entity: Robert Bosch LLC

Responsibilities

This role spearheads the development and optimization of the machinery for efficiently training, optimizing, testing, and releasing end-to-end AI-based products for Autonomous Driving Systems across various trim levels. Key duties include defining the technical roadmap, overseeing the design and development of the AI machinery, and guiding the transition from research prototypes to production-ready solutions.