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# Full Stack Software Engineer

- **Company:** Applimation, Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,700.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Cloud Storage, Data Centers, Information Engineering, Software Debugging, Distributed Systems, Elasticsearch, Monitoring of Systems, Python (Programming Language), PostgreSQL, Machine Learning, Prometheus, Web Application Frameworks, ReactJS, Grafana, Backend, Kubernetes, Optimization Algorithms, Restful APIs, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://www.themuse.com/jobs/apple/full-stack-software-engineer-ml-compute-capacity-3f3117

## About the Role

Experience operating Kubernetes at production scale - including scheduling, resource management, and cluster debugging

Familiarity with accelerator utilization patterns across ML training and inference

Strong interest with capacity planning, cost attribution, or FinOps systems

Minimum Qualifications

5+ years of experience in relevant areas

Proficiency in Python for production backend and data engineering work

Experience building data pipelines and crafting robust queries over large-scale, multi-source data (e.g., Trino, PostgreSQL, Elasticsearch), Experience designing and building RESTful APIs and working with cloud storage technologies

Experience with modern web frameworks like React

Experience with observability tools (e.g., Prometheus, Grafana) or equivalent monitoring systems

Excellent problem-framing and problem-solving skills

Strong CS fundamentals

Bachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative field

## Description

As a senior engineer on the ML Compute Capacity team, you will design, build, and operate the production systems that ensure compute resources are optimally distributed throughout the company. You'll work across the stack - from data pipelines and backend services to APIs and interactive frontends - developing telemetry systems, optimization algorithms, policies, and intuitive tools for managing demand and improving efficiency across Apple's largest accelerator fleet. Our small, nimble team works in a high-autonomy, fast-paced environment, and we're passionate about digging into data patterns, laying out the performance characteristics of an entire distributed system, and knowledge sharing. If the opportunity to own and operate services that scale, stay highly available, and "just work" excites you, then please reach out to us!

Responsibilities:

Build and operate demand and capacity planning systems

Build data pipelines and telemetry systems that ingest, normalize, and serve fleet-wide utilization and cost data across multi-tenant and heterogeneous fleets

Develop observability infrastructure - monitoring, alerting, and dashboards - that surfaces real-time fleet health and efficiency signals

Drive innovation in forecasting, optimization, and supply chain management tooling that works at scale

Build end-to-end tooling - from data models and APIs to interactive dashboards - that distills complex data into actionable insights for leadership

Build self-service platforms with well-defined schema contracts and APIs, enabling ML teams, infrastructure engineers, and finance to balance usability, utilization, and costs

Engage cross-functionally with finance analysts, supply chain managers, data center operations, compute infrastructure engineers, and more


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