The posting
Summary
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something!
Description
As a Senior Staff/Principal Engineer on the Foundation Model Compute Infrastructure team, you will architect, build, and operate large-scale infrastructure powering foundation model training, fine-tuning, evaluation, and inference. You will tackle challenging problems in distributed scheduling, accelerator utilization, cluster management, fault tolerance, and large-scale job orchestration. You will work with cloud and hardware partners to bring new TPU generations into production and build the tools and services that enable researchers to launch, monitor, debug, and profile their workloads without needing deep infrastructure expertise. You'll develop model inference and fine-tuning services, build secure, scalable sandbox infrastructure for running AI agents, code execution, and reinforcement learning environments at massive scale, and work closely with foundation model researchers and engineers to improve performance, reliability, scalability, and developer productivity. This is a deeply hands-on technical leadership role. You will write, review, and debug production code, lead complex architectural decisions, and use modern AI-assisted development tools to accelerate engineering execution and raise the quality bar across the team.
Responsibilities
Lead by example through hands-on coding, debugging, and solving the team's most challenging architecture and implementation problems. Design and build distributed scheduling, quota, and capacity management systems to maximize accelerator utilization across diverse workloads and teams. Improve fault tolerance, reliability, and recovery for large-scale training and inference workloads spanning thousands of accelerators, including automated hardware failure detection and remediation. Architect and operate Kubernetes-based infrastructure, including accelerator provisioning, node lifecycle management, cluster orchestration, and autoscaling. Collaborate with cloud and hardware partners to qualify, integrate, and deploy new generations of TPU hardware. Design, build, and operate secure, high-density sandbox infrastructure for executing untrusted, model-generated code and AI agent workloads, with strong isolation, fast startup, and efficient resource utilization to support reinforcement learning (RL) training, agentic evaluation, and tool use. Build self-service developer tools, APIs, and observability systems for job submission, monitoring, debugging, and performance profiling. Design and develop scalable services for foundation model fine-tuning and inference. Partner with researchers, ML framework engineers, and security teams to translate evolving research requirements into robust production infrastructure. Mentor engineers, drive technical design reviews, and establish engineering and operational best practices across the team.
Minimum Qualifications
8+ years of experience designing and building distributed systems or large-scale infrastructure, with demonstrated technical leadership. Strong hands-on experience with Kubernetes, cloud infrastructure, and operating production systems at scale. Proficiency in Python, Go, C++, or other programming languages used for infrastructure and distributed systems. Experience with accelerator infrastructure and machine learning training or inference workloads. Excellent written and verbal communication skills, with experience authoring technical design documents and driving collaboration across teams.
Preferred Qualifications
Hands-on experience operating TPU, GPU, or other large-scale accelerator fleets. Experience scaling distributed training or inference workloads across thousands of accelerators. Familiarity with JAX, XLA, and distributed machine learning frameworks, including performance analysis and profiling. Experience developing LLM-based agents or AI-assisted developer and infrastructure operations tools. Deep knowledge of distributed scheduling, resource allocation, multi-tenant quota management, or cluster autoscaling.
Pay & Benefits
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 $216,200 and $394,000, 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.
EEO Statement
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
Accessibility
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Application Deadline
Apple accepts applications to this posting on an ongoing basis.
