Principal Engineer, ML (VLA Automated Driving)

We are CARIAD, an automotive software development team with the Volkswagen Group. Our mission is to make the automotive experience safer, more sustainable, more comfortable, more digital, and more fun. To achieve that we are building the leading tech stack for the automotive industry and creating a unified software platform for over 10 million new vehicles per year. We’re looking for talented, digital minds like you to help us create code that moves the world. Together with you, we’ll build outstanding digital experiences and products for all Volkswagen Group brands that will transform mobility. Join us as we shape the future of the car and everyone around it.

​Role Summary:

​The Principal Engineer, ML (VLA Automated Driving) is the technical anchor for Vision-Language-Action (VLA /VLAM) models for our Level 2++ to Level 4 Automated Driving stack.

This role defines the technical direction for VLA-based driving across model architecture, training strategy, data flywheel, evaluation, and embedded deployment. The Principal Engineer bridges multimodal foundation-model advances with the realities of real-time, safety-critical automotive systems and helps turn promising research into robust in-vehicle capability.

This role also serves as the technical champion for applying GenAI and agentic AI to engineering workflows, identifying and scaling high-value use cases across model development, data flywheel, evaluation, and engineering productivity.

This is a highly cross-functional leadership role spanning model, data, evaluation, and deployment.

Role Responsibilities:

Technical Direction & Architecture

• Define the technical direction for VLA / VLAM-based automated driving
• Lead architecture decisions for multimodal driving models from perception and context to trajectories, actions, or driving intent
• Drive technical decisions on model adaptation, planning interfaces, fallback/arbitration, latency, and generalization

Model Development & Training Strategy

• Design, adapt, and evolve state-of-the-art vision-language-action / multimodal foundation models for automated driving
• Define training strategies across supervised learning, imitation learning, offline learning, synthetic data, and simulation-based approaches as appropriate
• Drive model quality across robustness, generalization, and complex traffic interactions

Data Flywheel & Platform Partnerships

• Define the data strategy needed to improve model performance quickly and systematically
• Partner with data and platform teams to establish a scalable flywheel across data selection, balancing, mining, labeling/annotation inputs, retraining, and evaluation
• Align data and training iteration loops to measurable performance outcomes and release readiness

Evaluation, Benchmarking & Deployment Readiness

• Define evaluation and benchmarking strategies for route-level and scenario-level driving performance
• Partner with embedded and systems teams to support deployment on target automotive hardware
• Drive model evaluation, error analysis, and generalization assessment across diverse driving scenarios

Technical Leadership & GenAI/Agentic Workflow

• Serve as a senior technical leader across engineering and partner teams, mentoring others and helping build long-term VLA capability in Mountain View
• Act as the technical champion for GenAI and agentic AI workflows within the team, identifying, validating, and helping scale high-value applications across model development, evaluation, data, and engineering productivity
• Establish technical standards and best practices for scalable, production-grade ML development in safety-critical systems

​General Skills:

• Deep expertise in end-to-end AI and foundation-model approaches for automated driving
• Strong software engineering skills and production mindset
• Excellent analytical, debugging, and technical decision-making skills
• Ability to lead highly complex cross-functional efforts in ambiguous environment
• Strong written and verbal communication skills
• Ability to collaborate effectively across teams, geographies, and time zones

​Required Specialized Skills:

• Deep expertise in foundation models, multimodal learning, and VLA / VLAM approaches for automated driving
• Strong background in transformers, vision models, multimodal fusion, and spatio-temporal modeling
• Hands-on experience with PyTorch or equivalent ML frameworks
• Strong experience developing and adapting large-scale ML models for real-world systems
• Experience or strong familiarity with AD/ADAS systems, including end-to-end driving models, world models, or VLA-based architectures
• Strong foundation in model evaluation, error analysis, and generalization across diverse driving scenarios

​Desired Skills:

• Experience with imitation learning, offline RL, reinforcement learning, or world-model-based training
• Familiarity with quantization, pruning, distillation, and hardware-aware optimization
• Familiarity with TensorRT, ONNX Runtime, or similar inference frameworks
• Experience deploying models on embedded or automotive-grade hardware
• Experience with simulation and large-scale evaluation pipelines for automated driving
• Understanding of automotive system constraints and safety considerations for ML-based ADAS/AD systems

​Workplace Flexibility:

• Calls, virtual meetings, and workshops overlapping with German and US business hours as needed
• Occasional domestic and international travel

​Years of Relevant Experience:​

• 12+ years of experience in applied machine learning, deep learning, robotics, or automated driving
• 5+ years of experience in one or more of the following: multimodal foundation models, computer vision, reinforcement learning, imitation learning, or AD/ADAS systems
• Strong candidates with equivalent industry experience will be considered

​Required Education:

• ​Master’s degree in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field

​Desired Education: 

• ​PhD in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field

Compensation

Salary range is dependent on factors such as geographical differentials, credentials or certifications, industry-based experience, qualification and training. In the city of Mountain View, CA, the salary range for this position is $235,520 - $323,044.

CARIAD, Inc. provides performance based merits and annual bonus along with a competitive benefits package. Benefits include medical, dental, vision, 401k with employer match and defined contribution plan, short and long term disability, basic life and AD&D insurance, employee assistance program, tuition reimbursement and student loan repayment plans, maternity and non-primary caregiver leave, adoption assistance, employee referral program and vacation and paid holidays. We also offer a unique vehicle lease program that covers registration and insurance fees. 

CARIAD is an Equal Opportunity Employer.  We welcome and encourage applicants from all backgrounds, and do not discriminate based on race, sex, age, disability, sexual orientation, national origin, religion, color, gender identity/expression, marital status, veteran status, or any other characteristics protected by applicable laws. 

Employment with Cariad Inc. is contingent upon the successful completion of this screening process. We emphasize the importance of compliance with export control and sanctions laws as a fundamental aspect of our operations. Our company is dedicated to adhering to these regulations to ensure the lawful and ethical conduct of our business activities. Employment with our company is contingent on either verifying U.S. citizenship or U.S. lawful permanent resident status or obtaining any necessary license or confirming the availability of an applicable exemption or license exception. You, the applicant, will be required to answer certain questions for export control purposes, and that information will be reviewed by compliance personnel to ensure compliance with federal law. Cariad Inc. may choose not to apply for a license or use an applicable license exception (if available) for such individuals whose access to export-controlled technology or software source code may require authorization and may decline to proceed with an applicant on that basis alone.

 By submitting your application, you acknowledge and agree to participate in the export control and sanctions compliance screening process. Your cooperation in this matter is essential to our shared success and the integrity of our operations. Thank you for your understanding and commitment to upholding these important standards.