Senior AI/ML Cloud Hardware Systems Engineer

Amazon Web Services (AWS); Cupertino (CA); On-site; USD 174,000 - 235,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. - D63 in Cupertino is seeking engineers to design and operate AWS-backed server hardware for AI/ML workloads. You will contribute to high-performance, scalable cloud platforms, influencing both hardware choices and accompanying software tools.

You will work across teams to deliver robust, cost-efficient systems for multi-billion-dollar AI models. The role emphasizes working with C++, Python, and low-level architectures, with a focus on reliability, scalability, and

Qualifications

• BS in CS/CE or related technical field required.
• 4+ years of programming with modern languages (C++, C#, Java, Python, Go).
• Experience designing or architecting scalable server systems.
• Knowledge of x86/ARM architectures and PCIe interfaces.
• Proven debugging and diagnostic skills in complex hardware/software stacks.

Responsibilities

• Lead complex architectural problems for server systems and scale solutions.
• Decompose hard problems into actionable tasks and deliverables.
• Develop automation and AI-driven workflows to improve reliability.
• Collaborate across teams to implement high-performance cloud hardware.

Skills

C++

C#

Java

Python

Golang

PowerShell

Ruby

x86 architecture

ARM

GPU/FPGA

Linux knowledge

Education

BS in Computer Science or Computer Engineering

Master’s in Electrical/Computer Engineering (preferred)

Tools

x86 architecture

ARM

GPU/FPGA

PCIe

I2C

IPMI

SPI

Job description

Annapurna Labs (U.S.) Inc. - D63 in Cupertino is seeking engineers to design and operate AWS-backed server hardware for AI/ML workloads. You will contribute to high-performance, scalable cloud platforms, influencing both hardware choices and accompanying software tools.

You will work across teams to deliver robust, cost-efficient systems for multi-billion-dollar AI models. The role emphasizes working with C++, Python, and low-level architectures, with a focus on reliability, scalability, and