Hire an MLOps Engineer

Owns the lifecycle around models: data pipelines, training and fine-tuning workflows, deployment, versioning, monitoring, and the automation that keeps it all reproducible. The role is accountable for concrete production deliverables, including reproducible ml pipelines, model deployment & serving, drift & quality monitoring. The trial scope names the output, reviewer, and acceptance evidence before work starts.

This role is usually the right hire when models are deployed by one person, from their laptop, bravely; nobody notices quality degrading until customers do; training runs are unreproducible folklore. On the matching call, an engineering lead checks the boundary against adjacent roles so you do not hire an impressive title for the wrong bottleneck.

Profiles show relevant work history, technical interview evidence, role-specific capabilities, and meaningful certifications where they exist. We then help you interview against your own architecture and failure cases. The final check is a paid one-week trial in your repo or approved data environment, not a generic coding puzzle.

The trial is scoped around committed work your team already needs. For this role, a useful first week can include audited your current model path to production; put version control around models and data; stood up basic drift and health monitoring; documented the one-command redeploy. You keep the work whether or not the engagement continues.

Published dedicated rates start at $3,200 per month, or $20 per hour for Time & Material work. Senior rates are $4,800 per month or $30 per hour. The trial is paid at the same published rate, with no deposit or conversion fee.

You can stop after the paid trial or request a free replacement during the engagement. Work continues month to month with no long-term lock-in. NDA and IP assignment are completed before onboarding, access is scoped to the work, and everything produced belongs to you.