Preferred location: Munich, Germany
Start date: As soon as possible
Duration: indefinite

NXP Semiconductors

NXP Semiconductors N.V. (NASDAQ: NXPI) provides High Performance Mixed Signal and Standard Product solutions that leverage its leading RF, Analog, Power Management, Interface, Security and Digital Processing expertise. These innovations are used in a wide range of automotive, identification, wireless infrastructure, lighting, industrial, mobile, consumer and computing applications. A global semiconductor company with operations in more than 35 countries, over 45.000 employees and a revenue of over $10 billion.

Department

As a member of the CTO organization, you’ll join NXP’s team of specialists to lay the groundwork for product innovation. Teams within the CTO organization supply the company with the advanced ideas and solutions for products that sense, think, connect, and act – while always collaborating with internal and external stakeholders to meet customer objectives. This role gives you the authority and opportunity to enable NXP’s colleagues, customers, and partners to create breakthroughs in Edge AI that advance the world.

The work is performed in the AI Competence Center of NXP at the Central Technology Office (CTO), embedded in NXP’s global AI-activities. The AICC is the partner of business lines to identify, develop, benchmark, and enable disruptive Edge AI solutions on NXP-systems. You will be part of an exciting community that works on state-of-the-art technology and beyond.

Exciting successful projects that have been run at NXP in the context of Edge AI are Software- and Hardware-Aware Neural Architecture Search (NAS), Mixed-Precision Quantization in the context of NAS, machine learning protection by model watermarking, and others.

Responsibilities

• Support relevant AI/ML use cases from NXP business lines regarding highest task performance, lowest resource cost, and derive both, future hardware requirements, and required software enablement features
• Identify, develop, evaluate, and integrate methods for neural network optimization and deployment, e.g., pruning, know-ledge distillation, mixed precision quantization, compression, running on a variety of resource-constrained inference nodes leveraging NXP-IP and NXP software environments
• Investigating how these methods can be brought into a larger NXP framework even for data-free optimization of neural networks
• SW-integration of above methods and neural networks in larger applications, open-source frameworks, and compelling demonstrators
• Methodological approach for keeping track of state-of-the-art in the relevant field
• Interaction with NXP application partners in business lines

Your Profile and required competencies

• University degree: BSc, MSc, or PhD in a technical specialization, Computer Science preferred, Electrical Engineering or relevant disciplines, with significant exposure/involvement with Machine Learning, Edge AI, and Embedded Systems 
• 6+ years of experience in software engineering in the industry using standard development tools (e.g., git, bitbucket, unit test driven development, using CI/CD, etc.) 
• Excellent track record in embedded machine learning and Edge AI (publications, hands-on experience, projects, etc.) 
• ​Affinity and experience with embedded processors, software, and machine learning accelerators
• Broad experience with embedded software architectures, build systems, version control systems
• Broad experience with Operating systems GNU/Linux, embedded systems, development boards

Competencies we are looking for

• Flexibility in working with AI frameworks (TensorFlow, PyTorch), preferably via Python and C++ interfaces
• Familiarity with setting up and maintaining related ML development environments (Jupyter, TensorBoard, ClearML, docker, etc.)
• Understanding of AI deployment toolchains, portability, and inference engines (CUDA, TensorRT, TFLite, ONNXRT, etc.)
• Integration of external software libraries and components, including extension of build systems
• Solid programming experience of Python, C, C++, and scripting languages on Linux systems

Additional competencies you bring to stand out

• Experience with Deep Learning compiler frameworks for both, just-in-time, and ahead-of-time compilation (e.g., MLIR, tvm, ONNXRT, tflite, tflite for micro, tvm micro, etc.)
• ML-DevOps experience
• Experience with distributed compute frameworks (e.g., Ray) and frameworks for shared compute (e.g., Slurm)
• Knowledge of build systems (YOCTO, OpenEmbedded, etc.)
• Working with cross-compilation toolchains for ARM

You can send your reactions to: sebastian.vogel@nxp.com; AI Competence Center.

More information about NXP in Germany...