AI Software Engineer

AMD · Beijing, China · Engineering

mid machine learning AI Engineer ic Bachelor's · Posted Jan 30, 2026

About this role

AMD is hiring a mid-level AI Engineer in the machine learning function based in Beijing, China. The posting calls out experience with PyTorch, Linux, Incident Response, Embedded Systems. Listed education preference: a bachelor's degree or equivalent.

Role
AI Engineer
Function
machine learning
Level
mid
Track
Individual contributor
Location
Beijing, China
Education
Bachelor's degree
Department
Engineering
Posted
Jan 30, 2026
AI Summary
Mid-level SRE responsible for reliability governance, SLI/SLO standards, and KPI improvements for distributed training systems. Requires strong distributed systems debugging, PyTorch experience, GPU/accelerator fundamentals, and RDMA networking knowledge. Focus on fault detection, chaos engineering, incident response, and preventing reliability regressions at scale.
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Job description

from AMD careers


WHAT YOU DO AT AMD CHANGES EVERYTHING 

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.  




Responsibilities

  • Own reliability governance (standards, runbooks, SLIs/SLOs) and deliver KPI improvements (goodput/badput).
  • Productionize fast recovery paths: fault detection, isolation, membership change, and continuation without stop-the-world restarts.
  • Establish fault-injection/chaos and regression gates to prevent reliability regressions (GPU/NIC/node, comms, storage, maintenance).
  • Drive day-to-day incident response and root-cause analysis, converting learnings into preventative fixes.

Requirements

  • Strong software + systems engineering; can debug complex distributed failures end-to-end (Linux, networking, concurrency).
  • Hands-on large-scale distributed training experience (PyTorch Distributed/torchrun; common parallelism patterns).
  • Solid accelerator fundamentals and operational debugging (GPU/NPU, drivers/runtime, profiling tooling).
  • RDMA networking and collective communication fundamentals (all-reduce/all-gather/all-to-all) and related failure modes.
    • This is an excerpt. Read the full job description on AMD careers →
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