ML Compute Efficiency Automation Engineer, Infrastructure & Planning
Core
Build self-correcting systems to automate ML compute operations, optimize hardware utilization, and reduce manual toil for Apple's ML organizations.
Role type
Senior IC infrastructure engineer (ML compute efficiency & automation)
Builds
Automated tooling for resource allocation, scheduling, and efficiency reporting
Domain
Cloud infrastructure & Machine Learning
Deliverable
production ML models
Required skills
Python, SQL, system design, automation, data modeling, infrastructure scaling, cross-team collaboration
Preferred skills
FinOps, capacity planning, anomaly detection, Django/Postgres, ML training/inference infrastructure
Technologies
Python, SQL, Tableau, Looker, Grafana, Django, Postgres, GPUs, TPUs, Apple Silicon
Responsibilities
Govern compute as code for resource requests and allocations; Hunt down ML inefficiency in inference and training workloads; Replace manual workflows with self-running systems; Build telemetry and anomaly detection for cost/efficiency; Re-architect processes to scale with usage; Create reusable tooling for the team
Seniority
Senior, hands-on IC