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Junior AI Deployment Health Scoring Developer

Nathan Yamamoto

Freelance · Job · Chicago

About the role

After a model deployment completes, something important happens: the deployment either stabilizes successfully or it starts showing signs of trouble. Error rate climbs slightly. Latency p99 drifts upward. Throughput drops. Memory footprint grows. None of these signals alone triggers an alert threshold, but together they describe a deployment that is going wrong slowly. Deployment health scoring — aggregating multiple post-deployment health signals into a composite score that reflects overall deployment stability — is how SRE teams catch slow failures before they become incidents. This is a freelance role — 20 hours per week. Our deployment platform manages 350 active model deployments. We have individual metric alerts. What we don't have is the composite health score that synthesizes them: a single number per deployment that reflects overall health and trends in the right direction — going down means something is getting worse, even if no individual metric has breached its alert threshold yet. As a junior developer, you'll build the deployment health scoring pipeline under senior SRE engineer supervision: collecting post-deployment metrics, computing composite health scores, and building the health score monitoring dashboard that deployment engineers use to spot slow degradation.

Responsibilities

  • Build post-deployment metric collection pipeline ingesting error rates, latency distributions, and throughput signals
  • Implement composite health score computation weighting and aggregating multi-metric deployment signals
  • Develop health score trend analysis detecting gradual degradation before individual metric alerts fire
  • Create health score monitoring dashboard showing score history per deployment with drill-down to contributing signals
  • Build health score alerting when composite score drops below healthy threshold or declines sharply
  • Maintain scoring pipeline as new deployment types and metric sources are added

Requirements

  • 1+ year of Python and SQL development experience
  • Basic familiarity with metrics, monitoring systems, or Kubernetes
  • Interest in MLOps, SRE, or deployment platform engineering
  • Attention to signal weighting accuracy and composite score interpretability
  • Reliable async communication for a freelance engagement

Benefits

  • Fully remote freelance — 20 hours per week
  • Flexible schedule
  • Competitive hourly rate
  • Mentorship from senior SRE engineers
  • Potential to expand scope

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Categories

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql pandas docker fastapi

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Job Type

Freelance

Level

Junior

Language

English

Salary Range

Under $60k / year

AI Expertise

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql pandas docker fastapi statistics

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