MLOps Engineer

Prime Solutions Group (PSG) is seeking a highly capable MLOps Engineer to design, automate, and operate secure, scalable machine learning pipelines and infrastructure across enterprise and mission systems. In this role, you will work at the intersection of ML engineering, Dev Sec Ops , cloud infrastructure, and cybersecurity—supporting advanced AI/ML workloads for defense and national security customers.

• Design, build, and maintain secure, automated ML pipelines for data ingestion, feature engineering, model training, validation, and deployment.
• Implement ML-aware CI/CD pipelines with unit tests, data validation, model validation, and promotion gates aligned to Dev Sec Ops  best practices.
• Automate model training, evaluation, and deployment using orchestration platforms (Airflow, Kubeflow, Prefect, Dagster, etc.) and model registries/experiment tracking tools.
• Containerize and deploy ML services (REST/gRPC microservices, batch, or streaming inference) using Docker and Kubernetes.
• Integrate monitoring, drift detection, and data quality checks into ML production systems.
• Partner with data scientists to transition models from experimentation to production, ensuring reproducibility and consistent environments.
• Collaborate with Dev Sec Ops , infrastructure, and security teams to meet PSG security baselines (image scanning, SBOMs, secrets management, IAM).
• Monitor and optimize ML training and inference performance, including GPU/CPU utilization and cloud cost efficiency.
• Troubleshoot complex issues across data pipelines, model services, cloud infrastructure, and ML orchestration tools.

• U.S. Citizenship (required)
• Active Top Secret Clearance or higher
• Bachelor’s degree in Computer Science, Data Science, Engineering, Applied Mathematics, or related field
• 2–4+ years of experience in at least one of the following:
  • MLOps or ML platform engineering
  • Dev Ops/Dev Sec Ops /SRE for ML workloads
  • Data engineering with ML integration
  • Applied ML in production environments
• Proficiency with Git and CI/CD tools (Git Lab CI, Jenkins, Git Hub Actions, etc.)
• Hands‑on experience with AWS, Azure, or GCP ML infrastructure
• Strong Python skills and experience with ML libraries (Num Py, pandas, scikit‑learn, PyTorch, Tensor Flow)
• Experience with Docker and Kubernetes
• Strong understanding of the ML lifecycle (feature engineering → training → validation → deployment → monitoring → retraining)
• Clear communication and cross‑functional collaboration skills

• Experience operating ML systems in production
• Hands‑on experience with:
  • MLflow, Weights & Biases, or similar model registries
  • Airflow, Kubeflow, Prefect, Dagster, or similar orchestrators
  • Feature stores or scalable data pipelines
• Experience integrating security into ML workflows (image/dependency scanning, policy‑as‑code)
• Familiarity with observability stacks (Prometheus, Grafana, EFK, Open Telemetry) and ML‑specific monitoring
• Knowledge of Zero Trust Architecture, NIST frameworks, and DoD STIG compliance
• Certifications:
  
  AWS ML Specialty, AWS Dev Ops, CKS, or related
• Experience supporting mission‑critical AI/ML systems for defense, intelligence, or critical infrastructure

• Competitive compensation & benefits
• Professional development & tuition assistance
• Collaborative, mission‑driven culture
• A small‑company environment where innovation happens fast
• Direct impact on high‑visibility government programs leveraging AI/ML

Salary range starts at $116,299, with the potential for higher compensation based on experience, skills, and mission needs.

Mid-Senior level
• Full‑time
• Engineering and Information Technology, IT Services and IT Consulting