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ML Platform Engineer - Forecasting Infrastructure

Hugo Lindqvist

Full-time · Mid-level · Los_Angeles

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About the role

The forecasting team has good ideas and not enough platform leverage. Training runs are inconsistent, feature pipelines are fragile, and deployment handoffs still depend on too much tribal knowledge. We are hiring the engineer who can put better rails around the whole system without slowing the scientists down.

Responsibilities

  • Stabilise training and deployment workflows for forecasting models
  • Reduce operational friction between research and production teams
  • Improve monitoring across data freshness, model versioning, and serving health
  • Support reproducibility standards for experiments and releases
  • Partner with data scientists on pipeline reliability improvements

Requirements

  • 4+ years in MLOps, platform, or infrastructure engineering
  • Python for workflow automation and debugging
  • Kubernetes and container orchestration in production
  • Airflow for scheduled data and model pipelines
  • GCP for managed infrastructure and storage
  • CI/CD for release workflows and environment consistency

Benefits

  • $126,000 - $149,000 base salary
  • Remote across North America
  • Equity and annual bonus
  • Dedicated budget for courses and certifications
  • A platform role with strong internal customer feedback

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Job Type

Full-time

Level

Mid-level

Language

English

Salary Range

$126,000 - $149,000

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes airflow gcp ci/cd

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