Staff AI Systems Engineer- Autonomous Driving

Company Description

We Are Bosch.

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry.

Let’s grow together, enjoy more, and inspire each other. Work #LikeABosch

• Reinvent yourself: At Bosch, you will evolve.
• Discover new directions: At Bosch, you will find your place.
• Balance your life: At Bosch, your job matches your lifestyle.
• Celebrate success: At Bosch, we celebrate you.
• Be yourself: At Bosch, we value values.
• Shape tomorrow: At Bosch, you change lives.

Autonomous Driving – Internship in Machine Learning

At Bosch, “Invented for Life” is what drives us and our vision of global future mobility. Bosch has an outstanding track record on pioneering key technologies worldwide which shapes the way we move. The next big milestone in our sight is to make autonomous vehicles a reality, bringing its benefits to today's roads.

We are looking for students in the machine learning and software development space who are interested in solving the hardest problems in the development and productization of automated driving with us.

Job Description

In this role, you will operate as a Staff AI Systems Engineer, setting technical direction across multiple teams, influencing architecture and engineering standards, and elevating technical capabilities across the organization.

We are seeking a Systems Engineer with strong leadership skills to build and enhance our AI-focused systems engineering and testing frameworks. In this role, you will guide the design, implementation, and evaluation of our Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) technologies. You will serve as the technical lead for a cross-functional team, integrating modern software development practices to help realize safe, reliable self-driving vehicles and empower our global R&D teams.

Responsibilities:

• Lead, mentor, and grow a collaborative, cross-functional AI systems team to build state-of-the-art development environments for robotics applications.
• Partner with management and technical leaders to define and implement a company-wide system design and deployment framework.
• Enhance the efficiency and clarity of our system development life cycle using automation, standard tooling, and transparent processes.
• Research, adopt, and integrate cutting-edge software engineering tools and processes into our development ecosystem alongside your team.
• Establish continuous testing standards across all domains by sharing best practices in process automation, tooling, and quality assurance globally.
• Provide daily technical guidance through design reviews, detailed technical documentation, pull request reviews, and hands-on testing

Qualifications

Basic Qualifications

• Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent practical experience).
• 5+ years of experience in systems engineering for automated driving, robotics, or complex software/hardware product releases.
• Hands-on experience with modern CI/CD pipelines, automated testing, and agile software development workflows.
• Demonstrated ability to guide cross-functional technical teams, manage stakeholder alignment across roadmaps and budgets, and establish engineering best practices.
• Experience defining requirement traceability and system specifications from high-level goals down to quantifiable performance metrics.

Preferred Qualifications

• In-depth knowledge of self-driving vehicle or robotics system architectures, including sensor processing, compute constraints, and on-board software stacks.
• Hands-on expertise across the ML lifecycle—including dataset curation, model training, fine-tuning, optimization, and real-world deployment for transformer-based or multimodal AI architectures.
• Experience with AI/ML frameworks and acceleration libraries such as PyTorch, PyTorch Lightning, ONNX, and TensorRT.
• Expertise in safety-critical system deployment under industry standards such as ISO 26262 and SOTIF, using KPI-driven evaluation frameworks.
• Experience with requirement traceability frameworks, system ontologies, and automated Operational Design Domain (ODD) taxonomy management.
• Experience designing and scaling distributed systems, cloud infrastructure, or orchestration tools (e.g., AWS, Azure, GCP, Airflow, Argo Workflows, Databricks).
• Familiarity with hardware/software testing environments, including SiL, HiL, and ViL setups.
• Working knowledge of real-time operating systems and environments such as Embedded Linux, QNX, RTOS, or ROS.

Additional Information

We offer a competitive base salary for this position with a range in US-California of --$185,000 - $215,000 along with an annual corporate bonus, and a long-term incentive bonus designed to reward sustained impact and contribution over time. Within the salary range, the 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.

Your well-being matters at Bosch! We offer a a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection.  Your Recruiter can share more details for this position during the interview process.

Learn more about our full benefits offerings by visiting: https://www.myboschbenefits.com/public/welcome.

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.

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