Staff MLOps Engineer at Prime Solutions Group, Inc.

Goodyear, Arizona, United States -

Full Time

Start Date

Immediate

Expiry Date

24 Apr, 26

Salary

167967.0

Posted On

24 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, ML Lifecycle Management, CI/CD Pipelines, Data Engineering, AWS, Python, Security Compliance, Model Performance, Infrastructure-as-Code, Mentoring, DevSecOps, Data Processing, Experiment Tracking, Model Registries, Incident Response, Agile

Industry

IT Services and IT Consulting

Description

Description Build, scale, and secure mission-critical AI/ML systems that matter. Prime Solutions Group (PSG), Inc. is seeking a Staff MLOps Engineer to lead how machine learning models and data-driven services are built, deployed, secured, and operated across multiple programs. This is a senior technical leadership role for an engineer who sets direction beyond individual projects, collaborates across disciplines, and operates with minimal supervision. Building on PSG’s mature DevSecOps foundation, you will define and drive enterprise MLOps best practices spanning the full ML lifecycle—from data ingestion and feature engineering through deployment, monitoring, drift detection, and retraining. This is a fast-paced, high-impact opportunity to deliver secure, scalable AI/ML solutions while mentoring technical teams and directly supporting U.S. national security missions. What You’ll Do Serve as a technical authority for MLOps and ML lifecycle management across multiple programs. Design and implement ML-focused CI/CD pipelines that automate data builds, training, evaluation, packaging, and deployment. Embed ML-specific validation, security, and compliance controls into pipelines, including: Data quality and schema validation Model performance and inference gates Security scanning, compliance checks, and SBOM generation Build and maintain Infrastructure-as-Code (IaC) for ML platforms supporting: CPU/GPU training and inference clusters Data, feature, and model artifact storage Feature stores, model registries, and monitoring stacks Harden ML and data infrastructure in AWS cloud environments, aligning with NIST, FedRAMP, and CIS requirements. Mentor MLOps, data engineering, and software teams on secure, reliable, and observable ML operations. Partner with data scientists to move models from experimentation to production, enabling: Reproducible training environments Experiment tracking and model registry workflows Optimized, production-ready inference services Lead or support incident response and risk analysis related to ML systems (e.g., data quality issues, model drift, security exposures). Support audits and compliance efforts by documenting ML pipelines, controls, and evidence. Stay current on MLOps, DevSecOps, and ML platform trends, contributing to PSG’s AI/ML roadmap. Requirements U.S. Citizenship Active Top Secret clearance or higher Bachelor’s degree in Computer Science, Engineering, Data Science, Applied Mathematics, or related field CompTIA Security+ CE (or ability to obtain within 30 days of hire) 7+ years of experience in one or more of the following: MLOps or ML platform engineering DevOps / DevSecOps / SRE supporting data or ML workloads Data engineering with production ML integration Applied ML in production environments Strong experience building secure CI/CD pipelines for ML and data systems Proficiency in Python and scripting for automation Hands-on experience with AWS cloud infrastructure Experience with ML and data tools such as: ML frameworks (PyTorch, TensorFlow, scikit-learn) Data processing tools (pandas, Spark) Experiment tracking or model registries (MLflow, SageMaker, Weights & Biases) Solid understanding of compliance frameworks (NIST 800-53, FedRAMP, ISO 27001) as applied to ML and data systems Demonstrated experience mentoring or leading technical teams Strong software engineering fundamentals (Git workflows, code reviews, testing) Preferred Qualifications Experience with containerization and orchestration (Docker, Kubernetes, Rancher) Familiarity with MLOps platforms and tooling: Workflow orchestration (Airflow, Kubeflow, Prefect, Dagster) Feature stores, data validation, and drift detection Experience with observability tools (Grafana, Splunk, Dynatrace, AppDynamics) for ML services Exposure to multi-cloud or hybrid ML environments Knowledge of Zero Trust security principles Experience in Agile/Scrum environments Experience building or integrating API-based ML services Exposure to Model-Based Systems Engineering (MBSE) environments Why Join PSG? At PSG, you’re not just filling a role—you’re shaping the future of secure, AI-enabled digital engineering. We combine the agility of a small business with the impact of supporting some of the government’s most advanced technology programs. We offer: Competitive compensation and benefits Professional development and tuition assistance A collaborative, mission-driven culture Direct impact on national security through secure AI/ML solutions Bring your MLOps expertise to PSG and help build the next generation of secure, intelligent, data- and model-driven platforms. Salary Description Salary range starts at $167,967 with the potential for higher compensation based on experience, skills, and mission needs.

Responsibilities

Lead the development and operation of machine learning models and data-driven services across multiple programs. Define and implement MLOps best practices throughout the ML lifecycle, ensuring secure and scalable AI/ML solutions.