> Markdown version of [/jobs/ext/4560901-ml-infrastructure-engineer-ml-compute-capacity](https://www.wearedevelopers.com/jobs/ext/4560901-ml-infrastructure-engineer-ml-compute-capacity). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# ML Infrastructure Engineer - ML Compute Capacity

- **Company:** Apple Inc.
- **Location:** Santa Clara, CA, United States
- **Salary:** $184,700.0
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Distributed Systems, Elasticsearch, Python (Programming Language), PostgreSQL, Machine Learning, Prometheus, Graphics Processing Unit (GPU), Grafana, Backend, Kubernetes, Machine Learning Operations, Data Pipelines
- **Published:** November 4, 2026
- **Apply:** https://www.juju.com/job/7_EC9304CCECB385D05C476A647C2603E4

## About the Role

If the opportunity to own and operate services that scale, stay highly available, and "just work" excites you, then please reach out to us!Minimum Qualifications7+ years of experience in relevant areasExperience with machine learning infrastructure on GPUs or TPUsProficiency in Python and/or Go for production backend and data engineering workExperience building data pipelines and crafting robust queries over large-scale, multi-source data (e.g., Trino, PostgreSQL, Elasticsearch)Experience with observability tools (e.g., Prometheus, Grafana) or equivalent monitoring systemsExcellent problem-framing and problem-solving skillsStrong CS fundamentalsBachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative fieldPreferred QualificationsExperience operating Kubernetes at production scale - including scheduling, resource management, and cluster debuggingExperience with modern web frameworks like ReactFamiliarity with accelerator utilization patterns across ML

## Description

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.