Machine Learning Systems Engineer, Siri Agent Modeling

Summary

Join the team redefining what a deeply personal and integrated assistant can be.

As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.

This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.

Description

As a Machine Learning Systems Engineer, you will work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference. You will be working across the ML stack at Apple, finding opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon. You will be joining a team that spans data, modeling, evaluation, deployment and working with engineers across ML infrastructure, inference, and framework teams. You will write production-level code to train and deploy models that will impact Apple's customers and enrich their lives. You are an ideal candidate if you: Are not afraid of CUDA OOM or NCCL errors

Minimum Qualifications

Experience in model lifecycle of training, evaluation, and deployment of models
Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers, CNN) and ML training loop
Strong proficiency in Python and ML framework such as PyTorch
Bachelor's degree in Computer Science, Engineering, or related discipline, or equivalent industry/project experience
Experience with agentic AI-assisted coding

Preferred Qualifications

Collaborative with experience working in large inter-teams projects
Expertise in ML and LLM optimization such as quantization, KV Cache, Speculative Decoding
Familiarity with ML training methodologies such as FSDP, DDP, and other parallelism
Experience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM.
Experience in optimizing LLM models and deploying LLM models
Proficiency in a compiled programming language (e.g. Swift, C/C++, Java)

Pay & Benefits — Cupertino, California, United States

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Application Deadline

Apple accepts applications to this posting on an ongoing basis.