MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred)

MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred)
Dayton, OH (On-site Preferred) | Remote Eligible (U.S.-based, Clearance-Ready)
Clearance-Eligible Role | Mission-Critical AI/ML Systems

About the Role

At Rackner, we build systems where advanced technologies move beyond prototypes and into real-world operational use.

We are seeking an MLOps Engineer to support the deployment and lifecycle management of AI/ML systems within a secure, mission-focused environment.

This is not a research role.

This is where models become reliable, deployable, and auditable systems.

You will operate at the intersection of:

machine learning

cloud-native infrastructure

distributed systems

…and ensure AI/ML systems are production-ready in environments where reliability and performance matter.

What You’ll Do

Own the ML Lifecycle (End-to-End)

Build and operate production-grade ML pipelines

Orchestrate workflows using Kubeflow, Airflow, or Argo

Implement model versioning, lineage, and reproducibility standards

Operationalize AI/ML Systems

Deploy models into secure and constrained environments
Transition workflows from experimentation → containerized pipelines → production systems
Enable both batch and real-time inference architectures

Engineer for Reliability

Design systems for reproducibility, auditability, and stability

Monitor model performance and system health using Prometheus, Grafana, OpenTelemetry

Detect and resolve issues such as model drift and system degradation

Build Cloud-Native ML Infrastructure

Deploy and manage Kubernetes-based ML workloads

Containerize pipelines using Docker

Support scalable training and inference workflows

Establish Data Discipline

Support feature engineering and dataset preparation

Implement data versioning and governance practices (e.g., lakeFS)

Apply metadata and data management standards

Create Repeatable Systems

Develop runbooks, playbooks, and documentation

Build systems that are operationally sustainable and transferable

What You Bring

Core Experience

Experience deploying ML systems into production environments

Strong programming skills in Python

Hands-on experience with:

ML pipeline tools (Kubeflow, Airflow, Argo)

Experiment tracking tools (MLflow, ClearML)

Infrastructure & Systems

Experience with Kubernetes and containerized systems (Docker)

Familiarity with CI/CD pipelines

Understanding of distributed systems and scalable architectures

ML Application Exposure

Experience working with:

LLMs or transformer-based models

Computer vision systems (YOLO, Faster R-CNN)

Focus on deployment and integration, not pure research

Mindset

Systems thinker who prioritizes reliability over novelty

Comfortable operating in complex, evolving environments

Focused on delivering real-world outcomes

Clearance Requirements

Active TS/SCI clearance strongly preferred

Candidates with an active Secret clearance may be considered and supported for upgrade

Candidates without an active clearance must be:

U.S. citizens

eligible to obtain and maintain a clearance

able to work in a CAC-enabled or secure environment

Note: Start timelines and work scope may vary depending on clearance status and program requirements

Why This Role Matters (What You Get)

This role is a career accelerator for engineers who want to:

Move beyond experimentation and own production systems

Work across ML, infrastructure, and deployment pipelines

Build in high-trust, secure environments

Develop high-demand MLOps expertise in constrained systems

Deliver systems that are used, not just built

Who We Are

Rackner is a software consultancy that builds cloud-native solutions for startups, enterprises, and the public sector. We are an energetic, growing team focused on solving complex problems through:

Distributed systems

DevSecOps

AI/ML

Cloud-native architecture

Our approach is cloud-first, cost-effective, and outcome-driven, delivering systems that scale and perform in real-world environments.

Benefits & Perks

100% covered certifications & training aligned to your role

401(k) with 100% match up to 6%

Highly competitive PTO

Comprehensive Medical, Dental, Vision coverage

Life Insurance + Short & Long-Term Disability

Home office & equipment plan

Industry-leading weekly pay schedule

Apply

If you’re an engineer who wants to move from building models → owning production systems, we’d like to connect.

 

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