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MLOps Engineer

Make model training, deployment, and monitoring repeatable and boring.

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Team
AI & Automation
Location
Delhi NCR / Hybrid
Arrangement
Hybrid
Type
Full-time
Level
Mid
Experience
3+ years
01

The role

Build the infrastructure around ML: experiment tracking, model registries, deployment pipelines, drift monitoring, and cost controls.

02

Requirements

  • Three or more years in MLOps, platform, or ML infrastructure roles
  • Experience with containerised model serving and CI/CD for ML
  • Comfortable collaborating with research-leaning ML engineers
03

Nice to have

  • Kubeflow, MLflow, Vertex, SageMaker
  • GPU cluster operations
Hiring
What happens next
01
We read it

A person reads every application. No keyword filter.

02
Reply

Within 5 working days if there is a fit.

03
Conversation

90 minutes with the people you would work with.

04
Paid trial

A real, scoped problem. Paid at contract rate.

Application

Send your work.
Skip the theatre.

Resume, a short note, and anything that shows how you think. Specifics beat adjectives.

  • Show something you built, not something you managed.
  • Scale, constraints, and trade-offs land better than adjectives.
  • A short note reads better than a long one.
info@bearsystems.in
Closes 28 October 2026 · MLOps Engineer
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