Responsibilities

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.

Key Responsibilities:

• Leads the 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.

Qualifications

Minimum Qualifications:

• 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

Preferred Qualifications:

• 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, TensorFlow, 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.

Hazardous Working Conditions/Environment

Not applicable.

Additional Information

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 co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct.

Requirements:

• U.S. Citizenship
• Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
• Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the applicant selected for hire is subject to pre-employment drug testing, and post-employment random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).

Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.

Testing Designated Position

This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.

Rockstar Rewards

Employees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance*, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company-funded pension plan* and may enroll in our 401 (k) savings plan with company match*. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

* Research Associates excluded.

**All benefits are dependent upon eligibility.

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Notice to Applicants

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual's relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $140,200.00/Yr.
Maximum Salary

USD $228,800.00/Yr.