Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems.
 
 All Riverside Research opportunities require U.S. Citizenship.
 

We are seeking a skilled AI/ML MLOps Engineer to support the deployment, monitoring, and maintenance of machine learning models in secure environments. This role focuses on operationalizing AI/ML workflows using MLOps best practices, with an emphasis on lifecycle management, observability, scalability, security, and incident response within mission-critical environments. The ideal candidate will have experience with cloud infrastructure, CI/CD pipelines, containerization, and secure DevSecOps environments.

• Design, implement, manage, and maintain scalable MLOps pipelines for deploying machine learning models into production.
• Automate testing, validation, and monitoring of AI/ML models to ensure high performance and reliability.
• Manage infrastructure using Infrastructure-as-Code (IaC) tools for secure and scalable deployments.
• Collaborate with data scientists and machine learning engineers to integrate models into end-user applications.
• Ensure compliance with security protocols for handling and processing classified data.
• Monitor model drift, performance degradation, and initiate retraining workflows as needed.
• Implement model versioning and experiment tracking to ensure reproducibility and traceability.
• Implement CI/CD pipelines to streamline development and deployment cycles.
• Document workflows, procedures, and infrastructure for reproducibility and auditability.
• Integrate and manage data ingestion and preprocessing pipelines aligned with secure data governance practices.

Degree in computer science, engineering, mathematics, or related field. A minimum of 8 years of related experience with a Bachelor’s degree, 6 years with a Master’s degree, 3 years with a PhD, or equivalent experience.

 

• 3+ years of experience in MLOps or DevOps roles supporting AI/ML deployments.
• Experience in conducting Test & Evaluation including evaluating and documenting the AI models and data across performance dimensions, informed by system and mission constraints.
• Experience with software development, software accreditation, software development best practices, code hygiene tools, and documentation.
• Proficiency in Python, Bash, and scripting languages for automation.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, and ONNX.
• Familiarity with observability tools such as Prometheus/Grafana, ELK Stack, OpenTelemetry, and Fiddler.
• Strong understanding of and hands-on experience with cloud platforms (AWS, Azure, GCP), container orchestration (e.g., Kubernetes, Docker), containerized pipelines and toolkits (e.g. Kubeflow), and Infrastructure-as-Code tools (Terraform, CloudFormation).
• Experience with CI/CD tools (GitLab CI, Jenkins, etc.) and MLOps platforms.
• Experience working in secure environments and handling classified data.
• Active TS/SCI clearance.

$105,000 - 220,000 This represents the typical compensation range for this position based on experience, location and other factors.

 
Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring.  Riverside offers comprehensive compensation and benefit packages to our employees.
Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran’s status or any other status legally protected by applicable federal, state, and local law.