Sr. Hardware Engineer - ML Acceleration, Annapurna Labs

Overview

Sr. Hardware Engineer - ML Acceleration, Annapurna Labs – AWS Utility Computing (UC)

AWS UC provides product innovations from foundational services such as S3 and EC2 to new product innovations across Compute, Database, Storage, IoT, Platform, and Productivity Apps. Annapurna Labs designs silicon and software that accelerates innovation with custom chips, accelerators, and software stacks to tackle technical challenges in cloud solutions.

We are seeking a Hardware Design Engineer to contribute to the definition, design and validation of AWS next generation ML Chips, Cards and server integration. As a senior member of our hardware team, you will participate in the design and execution of PCIe and SerDes topics to create customized platforms for AWS datacenters. On the Machine Learning Acceleration team you’ll design and optimize hardware for data centers, providing leadership in applying new technologies to large-scale server deployments to deliver a world-class customer experience. This is a fast-paced, intellectually challenging role that values high standards, continuous improvement, and a desire to push beyond today’s limits.

Responsibilities

• Define, design, and validate AWS next-generation ML chips, cards, and server integration.
• Lead the design and optimization of hardware in data center deployments, with emphasis on PCIe and SerDes topics.
• Collaborate with ODMs, IP silicon vendors, component suppliers, and internal design teams to triage, debug, and resolve cross-boundary issues.
• Work with cross-functional teams to apply new technologies to large-scale server deployments and improve product performance, quality, and cost.
• Provide technical leadership and mentorship within the hardware team.

Basic Qualifications

• Deep knowledge of PCIe interface Gen4 or above at chip and PCB levels.
• Deep understanding of transmission line theory, electromagnetics, SerDes, single-ended and parallel bus interfaces.
• Experience working with ODMs, IP silicon vendors, component suppliers, and internal design teams on debugging and issue resolution.
• Hands-on lab equipment experience (VNA, real-time scope, sampling scope) for electrical validation and characterization.
• Scripting skills to automate tests, log parsing, and data collection.
• Strong technical communication skills (verbal and written) for cross-functional collaboration.

Preferred Qualifications

• Experience with server hardware design, design validation, production tests, and signal integrity of high-speed interfaces.
• Knowledge of the product development cycle from concept to mass production.
• Strong analytical capabilities and the ability to work independently and drive tasks from start to completion.
• Ability to work cross-functionally with software teams to define and implement diagnostics for hardware validation at component, interface, and system levels.
• Experience with server architectures (x86/ARM).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: job duties include working safely, adhering to standards, communicating effectively, and complying with laws and company policies. Criminal history may affect eligibility. We will consider qualified applicants with arrest and conviction records in accordance with the Los Angeles County Fair Chance Ordinance. If you have a disability and need accommodations, please visit the provided information for more details.

Our compensation reflects the cost of labor across several US geographic markets. The base pay ranges from $143,300/year to $247,600/year, with additional compensation possible (equity, sign-on, etc.). For more information, visit the Amazon benefits page. This position will remain posted until filled. Applicants should apply via our internal or external career site.

Posted: August 27, 2025; Posted: July 30, 2025; Posted: June 10, 2025; Posted: September 18, 2025; Posted: April 4, 2025

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