Sr. Mechanical Engineer, Annapurna Labs, Artificial Intelligence Hardware
Amazon (AI roles) · Austin, Texas, USA
No salary listed. Estimated from 1377 salary-disclosed Engineering roles on this board: $200K–$300K (interquartile range; estimate, not the employer's figure).
Apply at Amazon (AI roles)Find your warm intro on LinkedInAbout the role
Annapurna Labs (our organization within AWS) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
As a member of the Annapurna ML/AI Mechanical Thermal Engineering team, you'll own the end-to-end thermal and mechanical architecture for ML/AI accelerator platforms — from initial concept through production deployment and ongoing fleet operations. You'll design mechanical and cooling solutions for some of the highest power-density silicon in the industry, balancing performance, reliability, cost, and operational efficiency at massive scale.
This is a technically challenging role requiring you to operate in ambiguity and at a fast pace. You'll collaborate across silicon design, electrical engineering, firmware, manufacturing, supply chain, and operations teams to deliver platforms that power AWS ML/AI services at global scale.
Key job responsibilities
As a Cloud Hardware Development Engineer (Thermal/Mechanical), you will:
Platform Ownership
Own the complete thermal and mechanical design for ML/AI accelerator platforms — from rack-level infrastructure down to chip packaging, including mechanical packaging, structural integrity, and interconnect systems
Define thermal and mechanical design requirements, establish design targets, and drive cross-functional alignment that enables parallel development across hardware, firmware, and software teams
Deliver production platforms through the full lifecycle: concept, design, analysis, prototyping, validation, manufacturing ramp, and fleet operations
Thermal & Mechanical Design
Design and optimize cooling solutions (air and liquid) for high-power-density ML/AI accelerators
Develop detailed CFD models, compact RC models, and structural FEA for SoC/package thermal analysis and mechanical integrity
Design rack manifolds, cold plates, and data center liquid cooling interfaces for at-scale liquid-cooled deployments
Develop and validate mechanical structures including chassis and enclosures for manufacturability, reliability, and serviceability. Owning tolerance stack-up analysis, GD&T, and DFM for high-volume manufacturing methods (stamping, bending, extrusion, die-casting)
Own mechanical design of integrating high-speed interconnect subsystems including cable cartridges, backplane connectors, and mating interfaces — defining alignment, gatherability, insertion force, and serviceability requirements
Perform structural FEA for shock, vibration, and transportation loads to ensure mechanical integrity across the product lifecycle
Fleet Operations & Reliability
Participate in on-call rotations monitoring fleet thermal telemetry for emergent issues
Perform root cause analysis of thermal and mechanical failures in production, implementing firmware updates, hardware modifications, or operational procedure changes
Cross-Functional Leadership
Drive design standardization
Engage with ODMs and component suppliers to drive design optimization, cost reduction, and supply chain resilience
Lead design reviews, mentor junior engineers, and contribute to the technical direction of the broader organization
Influence chip packaging decisions and establish validation methodologies
About the team
In 2015, Annapurna Labs was acquired by Amazon Web Services (AWS). Since then, we have developed products that power every layer of the AWS cloud, including AWS Nitro, Graviton processors, and custom ML/AI accelerators — Trainium for training and Inferentia for inference — that enable customers to build and run generative AI applications at scale.
The ML/AI MTE team is part of the Annapurna ML/AI hardware development organization. We design and deliver the thermal and mechanical systems for every generation of custom ML/AI accelerator hardware — from chip package through rack-level infrastructure. Our platforms operate at massive scale across AWS data centers globally, with current programs including next-generation Trainium and Inferentia systems featuring liquid cooling at scale. - BS degree in mechanical engineering or equivalent
- 7+ years industry experience in Mechanical and Thermal design in electronics packaging
- Experience in thermal and performance measurements and characterization on SoCs, Servers, or related Systems
- 3+ years of experience in SoC Thermal modelling and IC package transient thermal response
- Experience with chip package, system mechanical & thermal design for air-cooled and liquid-cooled systems
- Experience with tolerance analysis (stack-up/GD&T) and sheet metal or precision-machined component design for electronics packaging
- Experience with production fleet support: telemetry analysis, root cause analysis, and defining mitigation strategies
- Experience leading cross-functional technical projects spanning silicon, firmware, mechanical, and operations teams
As a member of the Annapurna ML/AI Mechanical Thermal Engineering team, you'll own the end-to-end thermal and mechanical architecture for ML/AI accelerator platforms — from initial concept through production deployment and ongoing fleet operations. You'll design mechanical and cooling solutions for some of the highest power-density silicon in the industry, balancing performance, reliability, cost, and operational efficiency at massive scale.
This is a technically challenging role requiring you to operate in ambiguity and at a fast pace. You'll collaborate across silicon design, electrical engineering, firmware, manufacturing, supply chain, and operations teams to deliver platforms that power AWS ML/AI services at global scale.
Key job responsibilities
As a Cloud Hardware Development Engineer (Thermal/Mechanical), you will:
Platform Ownership
Own the complete thermal and mechanical design for ML/AI accelerator platforms — from rack-level infrastructure down to chip packaging, including mechanical packaging, structural integrity, and interconnect systems
Define thermal and mechanical design requirements, establish design targets, and drive cross-functional alignment that enables parallel development across hardware, firmware, and software teams
Deliver production platforms through the full lifecycle: concept, design, analysis, prototyping, validation, manufacturing ramp, and fleet operations
Thermal & Mechanical Design
Design and optimize cooling solutions (air and liquid) for high-power-density ML/AI accelerators
Develop detailed CFD models, compact RC models, and structural FEA for SoC/package thermal analysis and mechanical integrity
Design rack manifolds, cold plates, and data center liquid cooling interfaces for at-scale liquid-cooled deployments
Develop and validate mechanical structures including chassis and enclosures for manufacturability, reliability, and serviceability. Owning tolerance stack-up analysis, GD&T, and DFM for high-volume manufacturing methods (stamping, bending, extrusion, die-casting)
Own mechanical design of integrating high-speed interconnect subsystems including cable cartridges, backplane connectors, and mating interfaces — defining alignment, gatherability, insertion force, and serviceability requirements
Perform structural FEA for shock, vibration, and transportation loads to ensure mechanical integrity across the product lifecycle
Fleet Operations & Reliability
Participate in on-call rotations monitoring fleet thermal telemetry for emergent issues
Perform root cause analysis of thermal and mechanical failures in production, implementing firmware updates, hardware modifications, or operational procedure changes
Cross-Functional Leadership
Drive design standardization
Engage with ODMs and component suppliers to drive design optimization, cost reduction, and supply chain resilience
Lead design reviews, mentor junior engineers, and contribute to the technical direction of the broader organization
Influence chip packaging decisions and establish validation methodologies
About the team
In 2015, Annapurna Labs was acquired by Amazon Web Services (AWS). Since then, we have developed products that power every layer of the AWS cloud, including AWS Nitro, Graviton processors, and custom ML/AI accelerators — Trainium for training and Inferentia for inference — that enable customers to build and run generative AI applications at scale.
The ML/AI MTE team is part of the Annapurna ML/AI hardware development organization. We design and deliver the thermal and mechanical systems for every generation of custom ML/AI accelerator hardware — from chip package through rack-level infrastructure. Our platforms operate at massive scale across AWS data centers globally, with current programs including next-generation Trainium and Inferentia systems featuring liquid cooling at scale. - BS degree in mechanical engineering or equivalent
- 7+ years industry experience in Mechanical and Thermal design in electronics packaging
- Experience in thermal and performance measurements and characterization on SoCs, Servers, or related Systems
- 3+ years of experience in SoC Thermal modelling and IC package transient thermal response
- Experience with chip package, system mechanical & thermal design for air-cooled and liquid-cooled systems
- Experience with tolerance analysis (stack-up/GD&T) and sheet metal or precision-machined component design for electronics packaging
- Experience with production fleet support: telemetry analysis, root cause analysis, and defining mitigation strategies
- Experience leading cross-functional technical projects spanning silicon, firmware, mechanical, and operations teams
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