Systems Development Eng (aws Generative AI & ML Servers), Aws Hardware Engineering Accelerators

Amazon Amazon · Big Tech · Cupertino, CA · Systems, Quality, & Security Engineering

This role focuses on designing, delivering, and operating AWS cloud offerings that enable high performance and scalability for AI/ML and HPC workloads, specifically targeting the backbone of Generative AI cloud infrastructure for training and inference. The Systems Development Engineer will work on server designs, from baremetal hardware up to userland software, ensuring price-performance improvements and architectural soundness for large-scale AI models.

What you'd actually do

  1. You will be a technical leader solving complex architectural problems which may not defined before hand.
  2. You will be owning the teams systems and work proactively in identifying deficiencies, writing tactical code to solve issues before they impact customers, and working with your team to scale the solution.
  3. You will decompose big difficult server system testability, reliability and diagnosis problems into straightforward tasks, components or features that you will lead to deliver yourself and through others in parallel.
  4. You will use combination of hardware, software, system designs, x86 architecture, processes, diagnosis and operations knowledge.
  5. Working with a variety of job roles (SDEs, SDETs, Hardware Engineers, TPMs, Managers, Principals) and groups (AWS Hardware Engineering, EC2, other AWS services) through server conception, test, launch, and operations.

Skills

Required

  • Systems development
  • Hardware engineering
  • Software engineering
  • Cloud computing
  • AI/ML infrastructure
  • HPC workloads
  • Server hardware architecture
  • System debugging
  • Problem-solving
  • Technical leadership
  • x86 architecture

Nice to have

  • Generative AI
  • LLM training
  • LLM inference
  • AWS services
  • EC2

What the JD emphasized

  • building the backbone of Generative AI cloud at AWS
  • build the future of the cloud for AI training and inference
  • industry leading work delivering continuous price performance improvements in the cloud for AI model training for multi billion variable LLMs
  • designing, delivering and operating AWS cloud offerings that enable high performance and scalability in AI/ML and HPC workloads
  • full technical stack - vertically from baremetal server hardware up to the software in userland
  • systems and software decisions impact the user
  • excellent systems debugger
  • complex architectural problems which may not defined before hand
  • owning the teams systems
  • writing tactical code to solve issues before they impact customers
  • scale the solution
  • big difficult server system testability, reliability and diagnosis problems
  • hardware, software, system designs, x86 architecture, processes, diagnosis and operations knowledge
  • AWS Accelerated server solutions for AWS Cloud

Other signals

  • AWS cloud offerings
  • high performance and scalability in AI/ML and HPC workloads
  • designing, delivering and operating AWS cloud offerings
  • next-generation AWS platforms
  • AWS Accelerated server solutions