2026 Campus - Embedded Machine Learning Engineer
Description For 2026 Campus - Embedded Machine Learning Engineer
NXP Semiconductors, a global leader in secure connectivity solutions for embedded applications, is seeking an Embedded Machine Learning Engineer for their 2026 Campus program in Beijing. This role combines cutting-edge machine learning with embedded systems development, offering an exciting opportunity for entry-level engineers to work on innovative solutions.
The position focuses on developing and optimizing ML inference engines for microcontrollers, requiring expertise in both machine learning frameworks (TensorFlow, PyTorch) and embedded systems programming. You'll be working on resource-constrained devices, optimizing models for low-power and memory-limited environments, and collaborating with cross-functional teams to integrate ML solutions into embedded systems.
As part of NXP's commitment to innovation and sustainability, you'll contribute to advancing technology in automotive, industrial IoT, mobile, and communication infrastructure markets. The company offers comprehensive career development opportunities, including online and offline learning programs to enhance your skills.
The ideal candidate should have a strong foundation in computer science or electrical engineering, programming proficiency in C++/Python, and a passion for machine learning and embedded systems. This role offers the perfect blend of theoretical knowledge and practical application in a collaborative, innovative environment at one of the world's leading semiconductor companies.
Responsibilities For 2026 Campus - Embedded Machine Learning Engineer
- Develop and optimize Embedded ML inference engines for microcontrollers
- Train and fine-tune machine learning models using TensorFlow and PyTorch
- Implement techniques to improve model performance on resource-constrained devices
- Collaborate with cross-functional teams to integrate ML solutions
- Conduct research on new machine learning techniques for Embedded ML applications
- Optimize machine learning algorithms for embedded systems
- Stay up-to-date with latest advancements in Embedded ML
Requirements For 2026 Campus - Embedded Machine Learning Engineer
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
- Strong experience with TensorFlow and PyTorch
- Proficiency in C, C++, and Python
- Extensive experience in embedded software development and machine learning
- Proven ability to read and understand technical articles and research papers in English
- Strong problem-solving skills and attention to detail
- Good communication skills and ability to work collaboratively
- Familiarity with embedded systems, microcontrollers, and RTOS
- Deep understanding of software development life cycle
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