MLOps Engineer — AI/ML Systems Deployment (TS/SCI Preferred)
Daytononsitemid
via Greenhouse
About this role
MLOps Engineer — AI/ML Systems Deployment
Location: Dayton, OH preferred
Work Arrangement: On-site preferred; remote may be considered for highly aligned, clearance-ready candidates able to support secure / CAC-enabled environments and travel as needed
Clearance: Active TS/SCI strongly preferred; active Secret may be considered for upgrade
Requirement: U.S. citizenship required
Build and Deploy Real-World AI Systems
Rackner is hiring an MLOps Engineer to move AI/ML systems from prototype → deployment → operational use in a secure, mission-focused environment.
This is not a research role—this is where models become reliable, repeatable, auditable systems that run in real-world conditions.
This role is ideal for engineers who want to:…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: python, kubernetes, docker, grafana, prometheus…
2
Level fit
This role is mid-level. We check your trajectory against it.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is based in Dayton. We weight your proximity and willingness to relocate.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
pythonkubernetesdockergrafanaprometheusopentelemetryairflowmlflowkubeflow
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