ML Ops Lead

FutureFit AI

Staff/Principal MLOps Engineer enhancing data architecture for AI workforce solutions. Driving reliability and observability while collaborating within a data-centric team environment.

Posted 6/8/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $195,000 - $220,000 per yearWebsite

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Evaluate current pipelines, data architecture, and ML workflows, producing a prioritized, opinionated plan for what needs to change and why
Design data and ML systems anchored in customer needs and built to last
Rebuild and harden pipelines, upgrade data architecture, and ship fixes directly
Raise the bar on observability, reliability, and data quality, establishing patterns and practices for the team.

Requirements

What you’ll need

Staff or principal-level experience in MLOps, data engineering, or ML platform/infrastructure
A track record of walking into complex, fast-grown systems, diagnosing the real problems, and materially improving them
Strong systems design ability: you can translate customer and product needs into durable, scalable architecture
Genuinely hands-on: you are as comfortable in the codebase implementing the fix as you are in the design doc
Deep experience building and operating production data pipelines and ML workflows at scale
Fluency with the modern data and ML stack and the cloud infrastructure it runs on.

Benefits

Comp & perks

Potential to convert to full-time role
Hybrid schedule available in NYC or Toronto

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

MLOpsdata engineeringML platformdata architecturedata pipelinesML workflowssystems designscalable architectureobservabilitydata quality

Soft Skills

problem diagnosishands-on implementationcustomer needs translation