Sr Software Engineer, Embedded Machine Learning

Job Description

Job Description

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 Sr Software Engineer, Embedded Machine Learning is responsible for designing, optimizing, and deploying machine learning models on high-performance embedded hardware platforms. This role focuses on translating machine learning models from training environments into production-ready implementations on embedded ML accelerators, including selection of efficient model architectures, quantization, runtime performance analysis, and functional validation.

The Sr Software Engineer, Embedded Machine Learning works independently on complex technical problems and collaborates closely with software, hardware, and systems teams to ensure reliable, real-time performance of machine learning workloads in production embedded systems.

Role Responsibilities

Embedded ML Development & Optimization

• Design, train, and optimize machine learning models for execution on embedded ML accelerators
• Quantize and convert machine learning models from training frameworks to embedded runtime environments
• Analyze and optimize runtime performance to meet real-time and hardware constraints
• Develop and maintain production-quality code and artifacts supporting machine learning deployment on embedded systems

Validation & Production Support

• Verify functional correctness and performance of deployed models on target hardware
• Debug and resolve performance and accuracy issues across the machine learning deployment pipeline
• Collaborate with cross-functional teams to integrate machine learning models into embedded systems
• Support deployed machine learning models in production, including performance monitoring, issue triage, and iterative improvement

Technical Collaboration & Continuous Improvement

• Contribute to continuous improvement of machine learning workflows, tools, and best practices
• Share technical knowledge and lessons learned with peers
• Document model behavior, performance characteristics, and deployment considerations to support collaboration and long-term maintainability

Years of Experience

• 6+ years of experience in machine learning, embedded systems, or performance-critical software development
• Production experience deploying and optimizing ML models on embedded or constrained hardware platforms

Required Education

• Bachelor's degree in Computer Science or Computer Engineering

Desired Education

• Master's degree in Computer Science or Computer Engineering

Skills

• Strong analytical and problem-solving skills applied to complex, real-time systems
• Ability to work independently on complex technical problems with limited supervision
• Clear written and verbal communication skills for collaborating with cross-functional partners
• Strong attention to detail and commitment to production-quality outcomes
• Demonstrated ability to learn new technologies and share knowledge with peers

Required Skills

• Training modern machine learning networks, including transformer-based architectures, for high-performance embedded hardware accelerators
• Quantization, deployment, and optimization of machine learning models for production embedded systems
• Profiling, debugging, and optimizing runtime performance of machine learning workloads on embedded ML accelerators
• Supporting machine learning models through deployment, validation, and iterative improvement on target hardware

Desired Skills

• Experience with Qualcomm Hexagon NPUs
• Experience working in ADAS or automotive embedded systems environments

Work Flexibility

• Some on-site work with embedded hardware required, driving test car

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 $181,414 - $249,046.

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.