Senior Principal Engineer – ADAS Data Loop & Flywheel

About the role

As the Senior Principal Engineer – ADAS & AV Data Loop & AI Flywheel, you will lead the architectural strategy, design, and execution of Bosch’s end‑to‑end continuous data engine that powers L2+ ADAS and autonomous driving stacks across multiple vehicle platforms.

Key responsibilities

• Define and execute the technical roadmap for the autonomous driving data engine, including fleet data loop automation, active‑learning pipelines, auto‑labeling, simulation, and MLOps tooling.
• Oversee architecture, development, and testing of the AI data flywheel and its integration with edge fleet triggers, cloud data lakes, model repositories, and automotive hardware.
• Collaborate with data engineering, cloud infrastructure, and embedded SOC teams to scale the AI machinery ecosystem.
• Establish rapid‑evaluation frameworks for benchmarking emerging multimodal AI solutions such as Transformers and Vision‑Language models.
• Guide transition of raw fleet logs into production‑grade training and auto‑labeling pipelines, optimizing runtime performance on automotive‑grade hardware.
• Implement automated validation workflows, scenario‑based testing (SIL/HIL), and continuous feedback loops aligned with ISO 26262 and ISO 21448 standards.
• Mentor and lead a team of AI scientists and software engineers, ensuring technical excellence in large‑scale AI systems.

Required profile

• Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering, AI or related field.
• 10+ years of software development and system architecture experience in ADAS or autonomous driving.
• Proven track record of taking AI‑based L2+ or higher autonomous systems into mass production.
• Deep knowledge of end‑to‑end AI architecture, model training algorithms, active learning, and data flywheel concepts.
• Experience with functional safety standards (ISO 26262, ISO 21448) applied to deep‑learning systems.

Required skills

• Python, C++ programming.
• Deep learning frameworks: PyTorch, TensorFlow.
• Model compression, quantization, and deployment on automotive SOCs.
• Cloud‑native distributed training: Ray, Kubernetes, Spark, Triton.
• MLOps / CI‑CD pipelines for petabyte‑scale datasets.
• Auto‑labeling frameworks, multimodal foundation models, 3D perception fusion.
• Simulation integration (SIL/HIL) and synthetic scenario generation.

What we offer

• Base salary range $240,000 – $320,000 per year.
• Annual bonus potential.
• Comprehensive health, dental, vision, HSA, FSA.
• 401(k) with employer match.
• Wellness programs, life and long‑term disability insurance.
• Paid time off, parental leave.