MLOps Engineer — AI/ML Systems & Deployment

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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