Sr./Staff ML Infrastructure Engineer, Compute (TPU Scheduling) - Foundation Model

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Description

As a Senior/Staff Engineer on the Foundation Model Compute Infrastructure team, you will lead the design and development of scheduling and orchestration systems for large-scale TPU workloads across multi-region clusters.

You will work on distributed systems that manage thousands of accelerators and enable reliable, efficient execution of large-scale training and inference jobs. This role spans scheduling algorithms, cluster lifecycle management, workload orchestration, reliability engineering, and performance optimization.

Responsibilities:

Design and evolve large-scale scheduling systems for TPU-based training and inference workloads across multi-region clusters

Build topology-aware, quota-aware, and fault-tolerant schedulers to improve utilization, fairness, startup latency, and reliability

Develop orchestration systems for distributed ML workloads running on Kubernetes and accelerator infrastructure

Improve cluster efficiency and operational scalability through automation of provisioning, resource management, quota workflows, and recovery handling

Collaborate closely with foundation model teams to support advanced distributed training and inference frameworks such as Pathways, Ray, and JAX-based workloads

Mentor engineers and influence architectural direction across Apple's distributed AI compute platform

Preferred Qualifications

Experience building schedulers, resource managers, or orchestration systems for distributed workloads

Experience with accelerator infrastructure such as TPU, GPU

Experience with distributed ML training or inference systems

Familiarity with frameworks such as JAX, PyTorch, TensorFlow, Ray, Pathways

Experience operating large-scale multi-tenant infrastructure in cloud or hybrid environments

Background in performance optimization, fault tolerance, or resource efficiency for large distributed systems

MS or PhD in Computer Science, Engineering, or related field

Minimum Qualifications

7+ years of industry experience building large-scale distributed systems or cloud infrastructure

Strong programming skills in Python, Go, C++, or similar systems languages

Extensive experience with compute infrastructure and workload scheduling

Strong expertise in distributed systems, scalability, reliability, and performance engineering

Experience with Kubernetes, container orchestration, or large-scale cluster management systems

Experience designing backend services or infrastructure platforms operating at production scale

Strong communication and collaboration skills across engineering and research teams

Bachelor's degree in Computer Science, Engineering, or related field

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 $175,000 and $308,500, 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.