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AI Serverless ML Engineer

Aiden Ferrari

Full-time · Job · Chicago

About the role

Most ML teams over-provision inference infrastructure because they can't predict demand. GPUs sit idle at 15% utilization during off-peak hours while the monthly bill keeps climbing. Our serverless ML platform solves this: automatic scaling from zero, cold start optimization, and intelligent request batching that maximizes GPU utilization without sacrificing latency SLAs. You'll build the serving infrastructure that makes serverless ML practical: container image optimization for fast cold starts, request queue management with priority-based batching, auto-scaling policies tuned to inference workload patterns, and the cost attribution system that shows clients exactly what they're paying for. Serverless inference is technically harder than serverless web — model loading takes seconds, not milliseconds. The engineering challenge is hiding that latency from users while keeping costs lower than always-on alternatives. If you enjoy squeezing efficiency out of infrastructure, this is your puzzle.

Responsibilities

  • Build serverless ML inference infrastructure with auto-scaling from zero
  • Optimize container cold starts for fast model loading
  • Design intelligent request batching for GPU utilization maximization
  • Implement cost attribution systems for per-client billing transparency
  • Define and maintain latency SLAs across different model serving tiers

Requirements

  • 3+ years in cloud infrastructure or ML platform engineering
  • Strong AWS experience including Lambda, ECS, and SageMaker
  • Docker optimization skills for container size and startup time
  • Python proficiency for platform tooling
  • Understanding of GPU inference workloads and cost optimization

Benefits

  • Fully remote — US time zones
  • Competitive salary with equity
  • $2,500 AWS certification and learning budget
  • Solving a core ML infrastructure efficiency problem

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Categories

MLOps & AI Infrastructure

Skills

python aws docker fastapi mlflow

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python aws docker fastapi mlflow airflow

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