At the NXP AI Competence Center, we are looking for an Embedded AI/ML Engineer passionate about EdgeAI and AI methodologies. Leverage your creativity for supporting our team in numerous EdgeAI projects. With your motivation and ideas, you contribute to develop yourself and the team skills further.

Are you inspired by machine learning, data, AI, high performance computing, and are you ready for a new challenge by maintaining the high-performance computing farm for AI training? Do you want to contribute to enabling stability and reliability of a GPU-cluster to support the experts in enabling real world applications and to gain experience developing innovative ideas and improving the system? Then you will want to be a part of the growing Artificial Intelligence Competence Center at NXP, a leading semiconductor company.

Our responsibilities are in the areas described below, where the exact responsibility of the candidate is determined taking his capabilities in mind:

• Identify, evaluate, and continuously track the latest technologies for Edge AI optimization software

• Enable optimization techniques such as quantization, pruning, distillation, neural architecture search, etc. both for discriminative AI (CNNs, RNNs, Transformers, etc.) and Generative AI (LLMs, Stable Diffusion, etc.) at the Edge.

• Identify, evaluate, and continuously track the latest technologies in AI for radar-systems (sensor fusion, advanced sensor functionalities, improved sensing capabilities, etc.)

• Build demonstrators and proof-of-concepts for EdgeAI applications and methodologies

• Address data domain generalization gaps over sensors, configurations, and datasets

• Methods are applied to vision, radar, audio, and other time-series-data for both Automotive as well as IoT & Industrial markets

• Executing the above in co-operative and EU-supported projects with external partners (universities, companies), and in NXP’s long term innovation program ("research”)

Your Profile

• University degree: MSc, PhD or PDEng in a technical specialism, like Computer Science or equally relevant.

• 10+ years of experience in (software) engineering, with significant exposure/involvement with Machine Learning / AI required

• Affinity and experience with embedded systems, software and NPU accelerators required.

• Experience with embedded software architectures, build systems, version control systems required.

• Broad experience with Operating systems GNU/Linux, embedded systems, development boards, and processors, and SW competencies required.

• Excellent communication skills in English (verbal /written) required. Experience in working in/with multi-site and multi-cultural projects/teams preferred.

Your Competencies

• To give you a feeling for the types of competences, some examples are:

• Track-record experience in working with AI frameworks (PyTorch, TensorFlow, etc.), required.

• Understanding of AI toolchains, deployment, portability and inference engines (CUDA, TensorRT, TFLite, ONNX, etc.) preferred.

• Familiarity with setting up and maintaining related ML-Ops development environments (MLFlow, ClearML, etc.) required.

• Knowledge of build systems (YOCTO, OpenEmbedded, etc.) beneficial, working with cross-compilation toolchains for ARM preferred.

• Solid programming experience of C, C++, Python and Bash programming languages on Linux systems required.

• Experience with on-device learning and federated learning appreciated.

• Familiarity with future technologies for extreme efficiency such as in-memory, analog, and neuromorphic computing beneficial.