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

Seattle, Washington, United States Machine Learning and AI 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 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 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 Compensation and Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $171,600 and $302,200, 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 will also receive benefits including comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and 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. Equal Opportunity & Accessibility 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. 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. Apple accepts applications to this posting on an ongoing basis. #J-18808-Ljbffr Apple Inc.