Radical Recruitment
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Role

Machine Learning Operations (MLOps) Engineer.

The bridge-builder

The bridge-builder who ensures models run not only in a lab, but reliably, scalably and securely in the cloud.

Hire a Radical MLOps EngineerRead the APAC research

Overview

Placeholder. The MLOps Engineer is the person you want when the prototype is working but the production story is still on a whiteboard. They turn experiments into systems that survive a real user base, a real bill, and a real incident.

Placeholder. Radical MLOps Engineers have been validated against APAC, so the judgement calls around observability, cost, and release rhythm come with a track record. They are comfortable on the boundary between platform, data, and ML teams.

Placeholder. Final founder copy to be imported here.

01·What this role does

What this role does

  1. 01
    Builds and runs CI/CD for models, features, and prompts
  2. 02
    Owns observability: metrics, tracing, data quality, and drift detection
  3. 03
    Designs retraining and rollback strategies that match the risk profile of the product
  4. 04
    Automates the boring parts of the lifecycle so the team can focus on the hard parts
  5. 05
    Advises on cloud cost and capacity before the bill becomes a surprise
02·Skills & experience

Skills and experience we look for

Strong Python and infra-as-code (Terraform / Pulumi / equivalent)
Hands-on with at least one major cloud (AWS / GCP / Azure) and Kubernetes
Experience with feature stores, model registries, and orchestration tools
Comfort with data engineering fundamentals: schemas, contracts, backfills
A security and compliance mindset, especially around AI Act obligations
03·How you engage

Typical engagement types

04·Why Radical
The APAC difference
Every Radical clears the APAC assessment before the shortlist.

APAC is our framework for evaluating the human qualities that make great AI professionals: Adaptability, Personality, Awareness, Connection. You are hiring for judgement, not only for a CV. Read the full method and findings in our research paper.

The best AI professionals do not sit on Toptal or LinkedIn Open To Work. They are already building. We know them, and we know how to reach them, because we have spent years inside this community.

Get in touch
Tell us what you need in a MLOps Engineer.

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