Senior Machine Learning Engineer III

Pacific Northwest National Laboratory•Richland, WA

About The Position

Pacific Northwest National Laboratory (PNNL) is seeking a Senior Machine Learning Engineer to implement, adapt, and mature research methods into software deployed primarily in unclassified sponsor environments. The role works closely with researchers in areas such as SI Assurance, agentic SI, and applied mathematics, translating underlying methods into reliable software implementations. The work spans experimental development, deployment, and continued improvement of software developed and maintained by the team. The engineer guides engineering decisions and contributes directly to shared codebases, collaborating with researchers, engineers, and stakeholders across the U.S. government. The work focuses on deep learning methods for large language models and computer vision, with opportunities to work with other models and methods. The position is within the AI and Data Analytics Division of PNNL’s National Security Directorate. The role requires the ability to obtain and maintain a federal security clearance and U.S. citizenship. Selected applicants are subject to a federal background investigation and pre-employment and random drug testing. The position is classified as a Testing Designated Position.

Requirements

Bachelor’s degree and at least 5 years of data science experience, or master’s degree and at least 3 years of data science experience, or Ph.D. and at least 1 year of data science experience.
Experience using Python with PyTorch, TensorFlow, or a similar deep learning framework.
Experience implementing or adapting methods for large language models, computer vision, or related deep learning applications.
Strong proficiency in Python and hands-on experience using PyTorch to implement and modify deep learning research methods, including investigating and debugging implementation and model behavior.
Professional experience developing and maintaining software in a collaborative codebase; significant contributions to established open-source software with a demonstrated record of use and review may also qualify.
Experience with software design, modular implementation, automated testing, version control, and code review.
Experience owning the design, development, and maintenance of substantial software components or capabilities and making implementation decisions within a project.
Experience collaborating with researchers and engineers to translate technical requirements into working software and make implementation decisions.
U.S. citizenship.
Ability to obtain and maintain a federal security clearance and meet eligibility requirements for access to classified matter.
Meet the stated drug-testing and illegal-drug non-use requirements for security clearance processing.

Nice To Haves

Experience leading software design or implementation efforts and mentoring other engineers.
Experience developing and evaluating agentic AI systems, including reusable tool interfaces, workflow state management, execution tracing, or systematic analysis of task outcomes and failures.
Experience interpreting technical literature or mathematical descriptions and collaborating with researchers to translate methods into working software, particularly in AI Assurance, agentic AI, or applied mathematics.
Experience developing modular, reusable packages or APIs, integrating them into larger systems, and using automated testing, version control, and collaborative development practices.
Experience deploying, maintaining, and improving ML or computational software in shared codebases, including reproducible environments, dependency management, automated build and deployment workflows, and incorporating user feedback.
Experience supporting national security missions.

Responsibilities

Design, develop, and implement methods, processes, and systems to analyze diverse data.
Apply statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and discover insights from structured or unstructured data.
Develop solutions informed by exploratory data analysis of complex, high-dimensional datasets.
Design, develop, and evaluate predictive models and advanced algorithms to extract value from data.
Implement, adapt, and mature research methods into reliable software, primarily for unclassified sponsor environments.
Collaborate with researchers to understand research methods and translate them into working software.
Guide engineering decisions and contribute to shared codebases with researchers, engineers, and stakeholders across the U.S. government.
Develop, deploy, maintain, and improve software and deep learning methods for large language models, computer vision, and related applications.
Transfer skills across application domains.