Senior Memory Subsystem Engineer for ML Chips

Amazon Web Services (AWS); Austin (TX); On-site; USD 159,000 - 215,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Job summary

Annapurna Labs (U.S.) Inc. in Austin, TX is seeking a Senior Memory Subsystem Engineer for the MLA Technology team to design, integrate, and validate next-gen ML chips, with emphasis on memory subsystems and IP bring-up.

You will collaborate with architects and software engineers, support debug in manufacturing and data centers, and develop scripts to scale operations across test benches and production fleets.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Systems Engineering, or related fields.
• 5+ years of practical semiconductor design work including full-chip and subsystem integration experience.
• Good knowledge of memory training, timing parameters and/or controller features
• Ability to create scripts (lua, bash, python, etc.) to accomplish functional day to day tasks.
• Knowledge of DDR/HBM/UCIe phy and controller related protocols

Responsibilities

• Collaborate with architects, design teams, and software engineers on our next generation ML chips
• Support on-going debug and operations of previous ML chips within manufacturing and the data center
• Dive deep into IP integration, packaging, silicon bring up, characterization, and validation of memory subsystems
• Independently develop the scripts you need to execute and collaborate with software engineers as your needs scale

Skills

Semiconductor design

Memory systems

Scripting

DDR/HBM/UCIe

Education

Electrical/Computer/Systems Engineering degree

Tools

Lua

Python

Bash

Job description

Annapurna Labs (U.S.) Inc. in Austin, TX is seeking a Senior Memory Subsystem Engineer for the MLA Technology team to design, integrate, and validate next-gen ML chips, with emphasis on memory subsystems and IP bring-up.

You will collaborate with architects and software engineers, support debug in manufacturing and data centers, and develop scripts to scale operations across test benches and production fleets.