DevOps Engineer (AI/ML Ops) at Prime Solutions Group, Inc.

Goodyear, Arizona, United States -

Full Time

Start Date

Immediate

Expiry Date

19 May, 26

Salary

133157.0

Posted On

18 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, DevSecOps, Cloud Infrastructure, Cybersecurity, CI/CD, Airflow, Kubeflow, Docker, Kubernetes, Python, AWS, Azure, GCP, Model Deployment, Security Baselines, Performance Optimization

Industry

IT Services and IT Consulting

Description

Description Transform cutting-edge machine learning research into real-world mission capabilities. Prime Solutions Group (PSG) is seeking a highly capable DevOps 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, DevSecOps, cloud infrastructure, and cybersecurity—supporting advanced AI/ML workloads for defense and national security customers. You will collaborate closely with data scientists, DevSecOps 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. Key Responsibilities 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 DevSecOps 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 DevSecOps, 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. Requirements 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 DevOps/DevSecOps/SRE for ML workloads Data engineering with ML integration Applied ML in production environments Proficiency with Git and CI/CD tools (GitLab CI, Jenkins, GitHub Actions, etc.) Hands-on experience with AWS, Azure, or GCP ML infrastructure Strong Python skills and experience with ML libraries (NumPy, pandas, scikit-learn, PyTorch, TensorFlow) 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 Preferred Skills / Experience 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, OpenTelemetry) and ML-specific monitoring Knowledge of Zero Trust Architecture, NIST frameworks, and DoD STIG compliance Certifications: AWS ML Specialty, AWS DevOps, CKS, or related Experience supporting mission-critical AI/ML systems for defense, intelligence, or critical infrastructure Why You’ll Want to Join PSG 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/MLOps expertise to PSG and help build the next generation of secure, intelligent, data- and model-driven mission systems. Salary Description Salary range starts at $97,665, with the potential for higher compensation based on experience, skills, and mission needs.

Responsibilities

The role involves designing, building, and maintaining secure, automated Machine Learning pipelines for data ingestion, training, validation, and deployment, while implementing ML-aware CI/CD pipelines following DevSecOps best practices. Responsibilities also include automating model orchestration, containerizing and deploying ML services using Docker and Kubernetes, and integrating monitoring and security measures into production systems.