3 дня назад
Software Engineer - Edge AI (Embedded ML)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer - Edge AI (Embedded ML): Developing and optimizing machine learning inference engines and models for microcontrollers and other resource-constrained embedded devices with an accent on TensorFlow, PyTorch, low-power optimization, and real-time performance. Focus on deploying AI models to embedded systems, researching Embedded ML techniques, and integrating solutions with cross-functional engineering teams.
Location: Beijing, China
Company
develops semiconductor and embedded technology solutions, including platforms for edge AI and embedded machine learning.
What you will do
- Develop and optimize embedded machine learning inference engines for microcontrollers.
- Train and fine-tune machine learning models with TensorFlow and PyTorch for resource-constrained devices.
- Improve model performance for low-power and memory-limited embedded systems.
- Integrate machine learning solutions into embedded products in collaboration with cross-functional teams.
- Research new machine learning techniques and tools for Embedded ML applications.
- Monitor technical articles and research papers to evaluate relevant advancements.
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 C, C++, or Python, with extensive experience in embedded software development and machine learning.
- Experience optimizing machine learning algorithms for embedded resource and performance constraints.
- Ability to read and understand technical articles and research papers in English.
- Strong problem-solving, attention to detail, communication, and collaboration skills.
Nice to have
- Experience deploying machine learning models to embedded devices.
- Familiarity with embedded systems, microcontrollers, and real-time operating systems.
- Knowledge of embedded software development life cycle practices and low-power, low-latency optimization techniques.
- Working knowledge of the NXP MCU SDK.
- Experience coordinating project deliverables and communicating with global teams across time zones.
Culture & Benefits
- Full-time employment.
- Collaboration with cross-functional and global engineering teams.
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