Senior Machine Learning Engineer III

Overview

Responsibilities

PNNL is seeking a Senior Machine Learning Engineer to implement, adapt, and mature research methods into software deployed primarily in unclassified sponsor environments. You will work closely with researchers in areas such as SI Assurance, agentic SI, and applied mathematics, understanding the underlying methods and translating them into reliable implementations. Your work will span experimental development, deployment, and continued improvement of software the team develops and maintains.

You will guide engineering decisions and contribute 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. Projects span research areas such as SI Assurance, agentic SI, and applied mathematics, with opportunities to work with other models and methods.

Key Responsibilities

• Designs, develops, and implements methods, processes, and systems to analyze diverse data.
• Applies knowledge of statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data.
• Produces solutions driven by exploratory data analysis from complex and high-dimensional datasets.
• Designs, develops, and evaluates predictive models and advanced algorithms that lead to optimal value extraction from the data.
• Demonstrates ability to transfer skills across application domains.
• 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.

Qualifications

Minimum Qualifications:

• BS/BA and 5+ years of data science experience -OR-
• MS/MA and 3+ years of data science experience -OR-
• PhD with 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.

Preferred Qualifications:

• 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.

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.

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence and Equal Employment Opportunity

Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.

Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug.  If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.

Security, Credentialing, and Eligibility Requirements

As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication.  The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.

Mandatory Requirements

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

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.

Click Here For Rockstar Rewards

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.

PNNL is seeking a Senior Machine Learning Engineer to implement, adapt, and mature research methods into software deployed primarily in unclassified sponsor environments. You will work closely with researchers in areas such as SI Assurance, agentic SI, and applied mathematics, understanding the underlying methods and translating them into reliable implementations. Your work will span experimental development, deployment, and continued improvement of software the team develops and maintains.

You will guide engineering decisions and contribute 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. Projects span research areas such as SI Assurance, agentic SI, and applied mathematics, with opportunities to work with other models and methods.

Key Responsibilities

• Designs, develops, and implements methods, processes, and systems to analyze diverse data.
• Applies knowledge of statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data.
• Produces solutions driven by exploratory data analysis from complex and high-dimensional datasets.
• Designs, develops, and evaluates predictive models and advanced algorithms that lead to optimal value extraction from the data.
• Demonstrates ability to transfer skills across application domains.
• 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.

Minimum Qualifications:

• BS/BA and 5+ years of data science experience -OR-
• MS/MA and 3+ years of data science experience -OR-
• PhD with 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.

Preferred Qualifications:

• 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.