Full Stack Software Engineer, ML Compute Capacity

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $184,700–$324,800 / yr
Posted: 7 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $203k

This role $255k

$162k most similar roles pay here $342k

This role pays more than 93% of similar roles. Most pay $184,900–$221,812 — the shaded band above. At the midpoint, this role pays about $255k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Full Stack Software Engineer, ML Compute Capacity

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Full Stack Software Engineer - ML Compute Capacity As a senior engineer on the ML Compute Capacity team, you will design, build, and operate production systems that ensure compute resources are optimally distributed across a large accelerator fleet. You will develop data pipelines and telemetry systems to ingest and serve utilization and cost data, while building observability infrastructure including monitoring, alerting, and dashboards. Your work involves creating end-to-end tools ranging from data models and RESTful APIs to interactive frontends using React to distill complex data into actionable insights. The role requires proficiency in Python for backend and data engineering, experience with Trino, PostgreSQL, Elasticsearch, and cloud storage technologies. You will solve problems related to demand planning, forecasting, and cost attribution within a distributed system environment to manage the infrastructure supporting large-scale machine learning training and inference workloads across multi-tenant and heterogeneous fleets.

Skills

Python Kubernetes React Trino PostgreSQL Elasticsearch RESTful APIs Prometheus Grafana Data Pipelines Cloud Storage Distributed Systems FinOps Monitoring Alerting

What you'll do

Build and operate demand and capacity planning systems for large-scale machine learning workloads.
Develop data pipelines and telemetry systems to ingest and serve fleet-wide utilization and cost data.
Create observability infrastructure including monitoring, alerting, and dashboards for real-time fleet health.
Design and implement optimization algorithms and tools for forecasting and supply chain management.
Build end-to-end tooling from data models and APIs to interactive frontends for leadership insights.
Develop self-service platforms with defined schema contracts to balance usability, utilization, and costs.
Manage the distribution of compute resources across multi-tenant and heterogeneous accelerator fleets.

What we're looking for

Bachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative field.
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 using tools like Trino, PostgreSQL, or Elasticsearch.
Experience designing and building RESTful APIs and working with cloud storage technologies.
Experience with modern web frameworks such as React.
Experience with observability tools like Prometheus and Grafana or equivalent monitoring systems.
Strong CS fundamentals and excellent problem-framing and problem-solving skills.