Engineer III, Machine Learning

Cariad, Inc. • Mountain View, CA

1d • $135,960 - $197,760

About The Position

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 Engineer III, Machine Learning contributes to the development of single-stage, end-to-end driving models for the ADAS system. This role supports the design, training, and evaluation of reinforcement learning–based models using world-model simulation environments and multi-modal sensor inputs such as camera and radar data.
This role applies modern machine learning techniques to help bridge research advances in multi-modal and foundation models with the practical requirements of real-time embedded deployment. The Engineer III, Machine Learning, works under guidance to help ensure models are robust, generalize effectively, and meet performance expectations across a range of driving scenarios.
This role collaborates closely with embedded engineers, data engineers, and MLOps/DevOps engineers to support scalable model training, evaluation, and deployment activities within the ADAS machine learning domain

Requirements

• Hands-on experience with deep learning techniques, including CNNs, transformers, spatio-temporal models, and modern foundation models
• Experience working with machine learning frameworks such as PyTorch (or equivalent)
• Computer vision experience applying modern deep learning techniques such as CNNs, DETR, and vision transformers
• Hands-on experience training reinforcement learning agents using simulation environments
• Familiarity with state-of-the-art machine learning concepts used in AD/ADAS systems, including end-to-end driving models, world models, and vision-language-action models
• Working knowledge of core machine learning principles and model development workflows
• 5+ years of experience in applied machine learning or deep learning, with experience working in AD/ADAS systems, reinforcement learning, or computer vision.
• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field
• Strong software engineering skills, including the ability to write clean, maintainable, and testable code
• Strong analytical and debugging skills applied to machine learning and data-driven systems
• Ability to work on moderately complex technical problems with guidance from more experienced engineers
• Clear written and verbal communication skills for collaborating with cross-functional partners
• Demonstrates strong analytical thinking, effective communication, and independent problem-solving across complex, multi-system environments.
• Takes ownership of technical deliverables and leads aspects of initiatives of moderate scope, facilitating cross-functional collaboration and contributing to key technical decisions. Applies specialized domain knowledge with sound business judgment to balance technical trade-offs and program goals.

Nice To Haves

• Familiarity with deep learning model optimization techniques such as quantization, pruning, and hardware-aware optimization
• Familiarity with inference frameworks such as TensorRT and ONNX Runtime
• Experience with simulation frameworks used in ADAS development
• Exposure to multi-modal machine learning models, including camera and radar fusion
• Basic understanding of automotive safety considerations related to machine learning systems
• Master’s degree in a related technical field

Responsibilities

• Support research and evaluation of single-stage, end-to-end ADAS model approaches and architectures
• Design and train end-to-end machine learning models for the ADAS stack under guidance from more experienced engineers
• Assist in developing training workflows and pipelines in collaboration with data engineering and MLOps teams
• Train models using reinforcement learning approaches within simulation or world-model environments and reinforcement learning frameworks
• Work with real and synthetic multi-modal sensor data (camera, radar, lidar) to support model development and experimentation
• Analyze model behavior and performance across diverse driving scenarios
• Evaluate and benchmark models against real-world driving use cases using established evaluation pipelines
• Support embedded engineering teams during model integration, optimization, and deployment on embedded hardware
• Collaborate with cross-functional teams to support ADAS machine learning initiatives
• Continue to develop technical skills and domain expertise through hands-on project work, code reviews, and knowledge sharing

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level