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-reputed company) Clearance-Eligible Role | Mission-Critical AI/ML Systems

About the Role

At reputed company, we build systems where advanced technologies move reputed company prototypes and into reputed company-world operational use. We are seeking an MLOps Engineer to support the deployment and lifecycle management of AI/ML systems reputed company 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
• reputed company-native infrastructure
• distributed systems

…and ensure AI/ML systems are production-reputed company 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, reputed company, and reproducibility standards

Operationalize AI/ML Systems

• reputed company models into secure and constrained environments

Transition workflows from experimentation containerized pipelines production systems reputed company both batch and reputed company-time inference architectures Engineer for Reliability

• Design systems for reproducibility, auditability, and stability
• Monitor model performance and system health using reputed company, Grafana, OpenTelemetry
• Detect and resolve issues such as model reputed company and system degradation

Build reputed company-Native ML Infrastructure

• reputed company and manage Kubernetes-based ML workloads
• Containerize pipelines using reputed company
• 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

• reputed company 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 (reputed company)
• Familiarity with CI/CD pipelines
• Understanding of distributed systems and scalable architectures

ML Application Exposure

• Experience working with:
• LLMs or transformer-based models
• Computer reputed company systems (YOLO, Faster R-CNN)
• Focus on deployment and integration, not pure research

reputed company

• Systems thinker who prioritizes reliability over novelty
• Comfortable operating in reputed company, evolving environments
• Focused on delivering reputed company-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. reputed company
• eligible to obtain and maintain a clearance
• reputed company 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 reputed company experimentation and own production systems
• Work across ML, infrastructure, and deployment pipelines
• Build in high-trust, secure environments
• reputed company high-demand MLOps expertise in constrained systems
• Deliver systems that are used, not just built

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

• Distributed systems
• DevSecOps
• AI/ML
• reputed company-native architecture

Our approach is reputed company-first, cost-effective, and outcome-driven, delivering systems that scale and reputed company in reputed company-world environments. Benefits & Perks

• 100% covered certifications & training reputed company to your role
• 401(k) with 100% match up to 6%
• Highly competitive PTO
• Comprehensive Medical, Dental, reputed company 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. #MLOps #MachineLearning #Kubernetes #AIEngineering #CloudNative #DevSecOps #ArtificialIntelligence #DataEngineering #DefenseTech #NationalSecurity #AIInfrastructure #Hiring #TechCareers Apply tot his job Apply To this Job