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AI Batch Inference Scheduling Engineer

Owen Goldberg

Full-time · Job · Los_Angeles

About the role

Kubernetes, Docker, and MLflow are the core of what we build at Emrex AI. If you've optimized batch inference scheduling under real cost and latency constraints, this role should be familiar territory. You'll build the scheduler that decides how batch inference jobs get queued and prioritized across our GPU fleet, balancing client SLAs against cost efficiency — right now that logic is a set of static priority rules that don't adapt well when load spikes. You'll join a cross-functional squad with defined sprints, clear ownership, and weekly syncs with leadership, working alongside the team that already owns our fine-tuning and inference cost optimization infrastructure.

Responsibilities

  • Build a batch inference scheduler balancing SLA guarantees and cost efficiency
  • Replace static priority rules with adaptive, load-aware scheduling logic
  • Integrate scheduling with existing Kubernetes and MLflow infrastructure
  • Monitor and tune scheduler performance under real production load
  • Partner with the inference cost optimization team on shared infrastructure

Requirements

  • Strong Kubernetes and Docker experience with production ML workloads
  • MLflow or equivalent experiment and deployment tracking experience
  • AWS infrastructure experience at scale
  • Experience with scheduling or resource allocation systems
  • Comfort working in a structured, sprint-based team

Benefits

  • Fully remote
  • Equity
  • Health and dental insurance
  • 401k matching
  • Conference and training budget

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Categories

MLOps & AI Infrastructure

Skills

python docker kubernetes aws mlflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python docker kubernetes aws mlflow

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