Senior Machine Learning Engineer

Overview

At PNNL,our core capabilities are dividedamongmajor departments that werefer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technologydirectoratesinclude National Security,Earthand Biological Sciences, Physical and Computational Sciences, and Energy and Environment.

In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex,real-world threats to our nation and the world.

The AI and Data Analytics Division, part of the NSD, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.

PNNL is seeking a Senior Machine Learning Engineer who has deep experience refactoring and modularizing research code for maintainability, extensibility, and reusability. The selected candidate must be able to collaborate effectively across research and engineering teams to align research goals with deployment requirements, and to develop packages, APIs, and interfaces that enable straightforward integration into mission-relevant environments. They should be fluent in Python and modern ML frameworks, and comfortable working with unstructured, experimental code.

• Leadsthe refactoring, modularization, and optimization of research code to improve maintainability, scalability, and production readiness.
• Collaborates closely with researchers to understand algorithmic intent and with engineers to ensure seamless integration into broader systems and workflows.
• Architects and develops tools, pipelines, and APIs that enable deployment into mission-relevant environments.
• Influences technical roadmaps and architectural decisions for AI/ML infrastructure.
• Evaluates and recommend emerging tools, frameworks, and practices to keep the team at the leading edge.
• Establishes and promotes best practices for translating research outputs into robust, production-quality software.
• Mentors junior staff on software engineering standards, code quality, and research-to-production workflows.
• Writes clear, well-documented code and leads code reviews to uphold team standards.
• Conducts work in secure environments with adherence to operational security requirements.

This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

• BS/BA and 5+ years of relevant work experience
  -OR-
• MS/MA and 3+ years of relevant work experience
  -OR-
• PhD with 1+ year of relevant experience

• Degree in computer science, engineering, mathematics, or a related field.
• Experience in research engineering, ML engineering, AI systems integration, or applied data science.
• Strong proficiency in Python and hands‑on experience with ML frameworks (e.g., PyTorch, Tensor Flow, Hugging Face).
• Demonstrated ability to navigate research codebases (e.g., Jupyter notebooks, unstructured scripts) and translate them into production‑ready components.
• Experience designing and deploying scalable ML pipelines or AI‑enabled tools in operational or mission‑critical settings.
• Excellent communication and cross‑functional collaboration skills, with the ability to bridge research and engineering teams.

Not applicable.

This position requires the ability to obtain and maintain a federal security clearance.

A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and…