Production ML Engineer: Foundation Models & Fast Inference

Apple Inc.; Seattle (WA); On-site; USD 185,000 - 309,000; Full time

Job summary

Apple Inc. in Seattle, WA is seeking a Software Engineer for the Foundation Model Services team to build production-grade solutions that run large language, vision, and speech models at scale.

You will partner with researchers to prototype inferences and optimize performance across hardware, while delivering reliable services to millions of users. We value hands-on coding, quick learning in a fast-moving field, and strong collaboration with product teams.

Qualifications

• 2+ years of industry experience shipping production software or ML systems.
• Proficiency in Go or Python.
• Experience deploying and operating services on a cloud platform using containers and Kubernetes/Docker.
• 5+ years of industry experience in ML technologies (LLMs, NLP, IR, Statistics).
• Bachelor’s degree or higher in Computer Science or related technical field.

Responsibilities

• Work closely with product teams to build production-grade solutions that launch models serving customers in real time.
• Partner with foundation model researchers to prototype and develop inference for cutting-edge model architectures, and build tools that help us understand and remove performance bottlenecks across different hardware and use cases.
• Write high-quality code, learn quickly in a fast-moving field, and grow your impact as you take on larger pieces of the system.

Skills

Production software

Go

Python

Cloud platforms

Kubernetes/Docker

ML technologies

Low-latency services

Communication & collaboration

Education

Bachelor’s degree in Computer Science or related field

Tools

Nvidia TensorRT-LLM

vLLLM

DeepSpeed

Nvidia Triton Server

Job description

Apple Inc. in Seattle, WA is seeking a Software Engineer for the Foundation Model Services team to build production-grade solutions that run large language, vision, and speech models at scale.

You will partner with researchers to prototype inferences and optimize performance across hardware, while delivering reliable services to millions of users. We value hands-on coding, quick learning in a fast-moving field, and strong collaboration with product teams.