Software Engineer - Edge AI
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Before you apply
LocationBeijing
Typefull-time
SeniorityMid
Company size10,000+ people
PostedOct 8, 2026 · 1mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field
Strong experience with TensorFlow and PyTorch for model training and deployment
Proficiency in programming languages such as C, C++, and Python
Extensive experience in embedded software development and machine learning
Excellent programming skills in at least one of the following: C, C++, or Python
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 the ability to work collaboratively in a team environment
Proven experience with deploying machine learning models to embedded devices, specifically for Embedded ML applications
Familiarity with embedded systems, microcontrollers, and real-time operating systems (RTOS)
Deep understanding of software development life cycle and best practices for embedded systems
Previous experience in a full-time role or significant project in a related field
Expertise in optimization techniques for low-power and low-latency machine learning models
Working knowledge of the NXP MCU SDK is a strong plus
Experience coordinating project deliverables and driving clear communication with global teams across time zones is a plus
Skills
TensorFlow
PyTorch
C
C++
Python
Embedded ML
RTOS
NXP MCU SDK
About the role
The AI Platform / Infrastructure role focuses on enabling the development, deployment, and operation of artificial intelligence solutions across the organization. It designs and maintains AI platforms, pipelines, and tooling to support scalable, reliable, and governed use of machine learning and AI systems.
Responsibilities
Responsibilities:
•
Develop and optimize Embedded ML inference engines for microcontrollers.
•
Train and fine-tune machine learning models using TensorFlow and PyTorch to be deployed on resource-constrained devices.
•
Implement and experiment with techniques to improve model performance on low-power and memory-limited devices.
•
Collaborate with cross-functional teams to integrate ML solutions into embedded systems.
•
Conduct research on new machine learning techniques and tools specifically for Embedded ML applications.
•
Optimize machine learning algorithms to meet the performance and resource constraints of embedded systems.
•
Stay up-to-date with the latest advancements in Embedded ML by reading and interpreting technical articles and research papers.
Requirements
Requirements:
•
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
•
Strong experience with TensorFlow and PyTorch for model training and deployment.
•
Proficiency in programming languages such as C, C++, and Python.
•
Extensive experience in embedded software development and machine learning.
•
Excellent programming skills in at least one of the following: C, C++, or Python.
•
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 the ability to work collaboratively in a team environment.
•
Preferred Qualifications:
•
Proven experience with deploying machine learning models to embedded devices, specifically for Embedded ML applications.
•
Familiarity with embedded systems, microcontrollers, and real-time operating systems (RTOS).
•
Deep understanding of software development life cycle and best practices for embedded systems.
•
Previous experience in a full-time role or significant project in a related field.
•
Expertise in optimization techniques for low-power and low-latency machine learning models.
•
Working knowledge of the NXP MCU SDK is a strong plus
•
Experience coordinating project deliverables and driving clear communication with global teams across time zones is a plus
About the company
More information about NXP in Greater China…