CARIAD
Tech / AI / Software
SrSoftwareEngineer,EmbeddedMachineLearning
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr Software Engineer, Embedded Machine Learning at CARIAD. Skills: Embedded Machine Learning, ML model optimization for embedded hardware, Quantization and conversion of ML models, Runtime performance analysis and optimization, Production deployment of ML models on embedded systems. designing, optimizing, and deploying machine learning models on high-performance embedded hardware platforms. translating machine learning models from training environments into production-ready implementations on em”
What You'll Achieve.
ensure reliable, real-time performance of machine learning workloads in production embedded systems; production-quality outcomes
Industry & Context.
analytical and problem-solving skills applied to complex, real-time systems; complex technical problems; Debug and resolve performance and accuracy issues
Some on-site work with embedded hardware required, driving test car, compliance with export control and sanctions laws, 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
What They're Looking For.
Must Have
Bachelor's degree in Computer Science or Computer Engineering, 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, 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
Nice to Have
Master's degree in Computer Science or Computer Engineering, Experience with Qualcomm Hexagon NPUs, Experience working in ADAS or automotive embedded systems environments
What You'll Do.
and deploying machine learning models on high-performance embedded hardware platforms
translating machine learning models from training environments into production-ready implementations on embedded ML accelerators
selection of efficient model architectures
runtime performance analysis
and functional validation
works independently on complex technical problems
collaborates closely with software
and systems teams to ensure reliable
real-time performance of machine learning workloads in production embedded systems
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
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
and iterative improvement
Contribute to continuous improvement of machine learning workflows
Share technical knowledge and lessons learned with peers
Document model behavior
performance characteristics
and deployment considerations to support collaboration and long-term maintainability
How You'll Work.
Team & Collaboration
collaborates closely with software, hardware, and systems teams; Collaborate with cross-functional teams to integrate machine learning models into embedded systems; Share technical knowledge and lessons learned with peers; Document model behavior, performance characteristics, and deployment considerations to support collaboration and long-term maintainability
Communication Scope
Clear written and verbal communication skills for collaborating with cross-functional partners
Full 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 r
Applying for this Sr Software Engineer, Embedded Machine Learning role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Greenhouse
- Create a Greenhouse profile before applying — it saves time across multiple applications.
- Upload your resume as a PDF; the parser handles it better than Word.
- Answer all knockout questions carefully — wrong answers auto-reject before a human sees you.
- Enable email notifications to track application status in real time.
ANONYMOUS · UNFILTERED
What do employees actually say about CARIAD?
Real rants from real employees. Read before you apply.