DevOps Engineer; AI​/ML Ops

Overview

Transform cutting-edge machine learning research into real-world mission capabilities. Prime Solutions Group (PSG) is seeking a highly capable Dev Ops Engineer (AI/ML Ops) 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.

You will collaborate closely with data scientists, Dev Sec Ops  engineers, and system architects to transition ML models into robust, production-ready services. This is a high-impact role supporting next-generation, AI-enabled digital engineering environments.

• 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

At PSG, you’re not just taking a job—you’re shaping the future of AI-enabled digital engineering and national security. We offer:

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

Bring your AI/ML Ops expertise to PSG and help build the next generation of secure, intelligent, data- and model-driven mission systems.

Salary range starts at $97,665
, with the potential for higher compensation based on experience, skills, and mission needs.