Director, Simulation and Evaluation - Autonomous Driving

Bosch USA; Sunnyvale (CA); On-site; USD 240,000 - 300,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Wellness programs

Paid time off

Job summary

Bosch USA in Sunnyvale, CA is seeking a Director for Simulation and Evaluation to lead the Global AI Backbone, architecting multi-level simulation ecosystems to train, evaluate and validate Foundation Models for ADAS. You will bridge high-fidelity sensor simulation with world models and define a global ecosystem enabling continuous development and deployment.

You will mentor a cross-functional team of SWEs, data scientists, and ML experts, drive safety-focused evaluation standards, and translate

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, Statistics, Physics, or a related quantitative field.

Responsibilities

• Lead AI Simulation & Foundation Model Strategy: Define the roadmap for high throughput, closed-loop simulation.
• Research and propose new methodologies to assess quality, safety, and realism of ML models for training, evaluation and validation of L2++ and L4 stacks.
• Architect Evaluation Frameworks: Build infrastructure and tools for rapid iteration of Foundation Models, ensuring gains in fleet-wide performance.
• Drive Generative AI Innovation: Lead the development of World Models to predict/generate complex edge cases; build data pipelines for signal discovery, labeling, and metrics.
• Production Release Authority: Establish the gold standard for evaluation informing SoP and model release decisions; translate data into exec strategy docs.
• Global Technical Leadership: Lead, mentor and inspire a cross-functional global team of SWEs, Data Scientists, and ML experts with rigorous validation.

Skills

AI simulation leadership

L2/L4 ADAS

C++

Python

World Models / Generative AI

Data-driven decisions

Executive communication

Education

Master's or PhD in CS/EE/ML/Statistics/Physics

Tools

CUDA

Simulation frameworks

Job description

We Are Bosch.At Bosch, we shape the future by inventing high-quality technologies and services that spark

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

• 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.

“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 Director for Simulation and Evaluation, you will sit at the center of the Global AI Backbone, architecting the multi-level simulation ecosystems required to train, evaluate and validate next-generation Foundation Models. You will bridge the gap between high-fidelity sensor simulation and generative world models, ensuring our AI systems are statistically proven to be safe and robust before hitting the road. This is a global role that requires you to define and manage a global simulation and evaluation ecosystem that enables continuous development and deployment of our ADAS systems.

Key Responsibilities

• Lead AI Simulation & Foundation Model Strategy: Define the roadmap for high throughput, closed-loop simulation.
• Research and propose new methodologies to assess the quality, safety, and realism of ML models used for training, evaluation and validation of L2++ and L4 automated driving stacks.
• Architect Evaluation Frameworks: Build the infrastructure. Develop tools that allow for rapid iteration of Foundation Models, ensuring model improvements translate into measurable gains in fleet-wide performance.
• Drive Generative AI Innovation: Lead the development of World Models to predict and generate complex, realisticedge cases. Build data pipelines for signal discovery, data labeling, and metric computation based on large-scale simulations.
• Production Release Authority: Establish the "gold standard" for evaluation that informs SoP (Start of Production) and model release decisions. Translate complex simulation data into technical strategy documentation for executive decision-making.
• Global Technical Leadership: Lead, mentor and inspire a cross-functional global team of SWEs, Data Scientists, and ML experts, fostering a culture of rigorous statistical validation and innovative engineering.

Qualifications

Basic Qualifications:

• Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, Statistics, Physics, or a related quantitative field.
• 10+ years of experience in software engineering, with a specific focus on embedded systems, automotive, or robotics.
• 7+ years of experience leading complex software projects from concept to production within the ADAS or Autonomous Driving domain.
• Direct, hands‑on experience with L2++ or L4 system Start of Production (SoP), specifically overseeing simulation, testing, and validation protocols for high-stakes deployments.
• 5+ years of involvement with the development or evaluation of large-scale AI, LLMs, or World Models/Generative AI models for simulation and behavioral prediction.
• Expert-level understanding of multi-level simulation platforms, including high-fidelity sensorlevel simulation for perception and scalable object-level simulation for behavioral training.
• Proven mastery of data-driven report writing and technical strategy documentation designed for executive decision-making and safety case justifications.

Preferred Qualifications

Preferred Qualifications:

• 5+ years of experience with high-throughput simulation, GPU-accelerated technologies (CUDA), parallel computing, and Reinforcement Learning (RL).
• Mastery of C++ and Python. Experience building automated data pipelines for signal discovery, data labeling, and large-scale metric computation.
• 5+ years of experience managing and mentoring global, multi-disciplinary teams of Software Engineers, Data Scientists, and ML experts.
• Working knowledge of automotive industry safety standards and regulations (e.g., ISO 26262, SOTIF) as they apply to virtual validation.

Additional Information

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.

The U.S. base salary range for this full-time position is between $240,000-300,000. 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.

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