Function: Electrical Engineer (EE)/Computer Science
Level: Junior (not a senior role)
Scope:
System-level Electrical Engineering -- not a pure FPGA specialist role (FPGA is add on)
Ramp-up on FPGA related work and able to debug factory issues.
Key Requirements: Strong foundation in Schematic Design, Analog & Digital circuits
Hands-on lab experience is essential
Business-level English is a must
Education: Master's Degree from a top CS/ECE/EE program required; zero prior work experience acceptable.
Target start date: October with a training schedule.
Line of Business: HomePod

Master's degree in computer science, Computer Engineering or Electrical Engineering from a top university.
With a focus on AI/ML
Strong proficiency in a modern programming language system such as C++, ObjectiveC/Swift, or Rust. A demonstrated ability to quickly master new languages and platforms is highly valued.
Hands on with programming embedded system and using common interfaces such as I2C, SPI, UART, USB etc.
Hands on with scripting language Python/Lua/Bash and Linux
Design and verification experience of FPGA RTL components using System Verilog.
Experience of acting as a technical partner to internal customers. Need to translate vague requirements from teams into concrete engineering specifications.
Functional literacy in AI/ML concepts: Understand the fundamental lifecycle of machine learning (datasets, training vs. inference, evaluation metrics) and can discuss the engineering challenges involved.
Practical knowledge and operational experience using modern LLM AI tools such as ChatGPT/Claude CodeWebsite: [protected info] Facebook: HCLTech Vietnam | Facebook
Demonstrated experience in problem abstract and solving have the ability to navigate the ambiguity of a relatively complex issue, summarize and analyze.
Great communication skills in both English and Vietnamese.
Preferred qualifications:
Experience in modern MacOS programming (Swift, Swift UI)
Verbal communication in Chinese
Modern Altera FPGA experience
Hands-on experience building and deploying LLM or Agentic AI tools, and using them to drive proactive improvements in work efficiency