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AI Serverless Function Cold Path Profiler

Aiden Ferrari

Part-time · Job · Los_Angeles

About the role

Docker, Kubernetes and serverless inference are the core of what we build for teams running unpredictable AI workloads. Cold starts are our biggest source of customer complaints, and nobody on the team has time to properly profile where the latency actually comes from. You'll build the profiling tool that traces cold-start latency across the serverless invocation path and surfaces the biggest wins. This is a part-time role, roughly 20 hours a week, with one required in-office day for infrastructure planning syncs.

Responsibilities

  • Build profiling tools tracing serverless cold-start latency
  • Identify and document the highest-impact optimization opportunities
  • Partner with the infrastructure team on planning syncs
  • Prototype fixes for the most common cold-start bottlenecks

Requirements

  • 3+ years in cloud infrastructure or platform engineering
  • Strong Docker and Kubernetes experience
  • AWS experience preferred
  • Available roughly 20 hours a week, one in-office day

Benefits

  • Part-time schedule with flexible hours
  • Prorated health insurance stipend
  • Hybrid setup, one office day per week
  • Path to full-time if scope expands

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Categories

MLOps & AI Infrastructure

Skills

python docker kubernetes aws

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AI Expertise

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Skills

python docker kubernetes aws

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