Overview

At PNNL, our core capabilities are divided among major departments that we refer 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 & Technology directorates include National Security, Earth and 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 Earth and Biological Sciences Directorate (EBSD) leads critical research in four areas: Atmospheric, Climate & Earth Sciences, Biological Sciences, Environmental Molecular Sciences, and Global Change. Our vision is to develop a predictive understanding of biological and Earth systems in transition. We aim to understand energy and material flows within the integrated Earth system; to understand, predict, and control the response of biosystems to environmental and/or genomic changes; and to   Model the Earth system from the subsurface to the atmosphere.

The Environmental Molecular Sciences Division is comprised of 18 interdisciplinary research teams focused on deciphering molecular-level interactions driving biological and environmental processes across temporal and spatial scales. Through computational analysis and modeling, these findings contribute to predictive understanding of how systems respond to environmental perturbations thus enabling solutions to the nation’s energy, environmental, and human health challenges. The division also manages the Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus that accelerates the research of scientists around the world by providing access to world-class expertise, instrumentation, and computational resources.

Responsibilities

The Computing, Analytics, and Modeling (CAM) Group at the Pacific Northwest National Laboratory is seeking a Computational Scientist experienced in building AI agents for scientific discovery. The successful candidate will support the BER mission by architecting, developing, and integrating AI agents that will advance Environmental Molecular Sciences Laboratory’s (EMSL) user-centric charter. The agents will perform reasoning and actionable decisions with workflows related to EMSL’s data transformations and modeling science capabilities. These agents will integrate these workflows with various instrument data pipelines to enable model-experiment (ModEx) integration and also drive autonomous experimentation at EMSL. The Environmental Molecular Sciences Laboratory (EMSL) is a premier national scientific user facility – supported by the U.S. Department of Energy’s Oﬃce of Biological and Environmental Research (BER) – oﬀering cutting-edge experimental and computational resources, with over 75 state-of-the-art instruments and capabilities. EMSL Users tackle critical molecular-to-mesoscale challenges aligned with DOE’s objectives, driving innovative and transformative science. Join us in shaping the future of scientific discovery and impact at PNNL.

The Environmental Molecular Sciences Division’s (EMSD’s) Computing, Analytics, and Modeling (CAM) group focuses on advancing the science of the Environmental Molecular Sciences Laboratory (EMSL) user facility and the mission science of its sponsor, the DOE Oﬃce of Science’s Oﬃce of Biological and Environmental Research (BER) mission, by delivering world-class capabilities and developments in computational science, data analytics and transformations, and modeling sciences. The group, which reports to the CAM Group Leader, works with researchers and staﬀ in EMSL’s other two science areas (Environmental Transformations and Interactions, or ETI, and Functional and Systems Biology, FSB) to deliver on EMSL’s three strategic science objectives: DigiPhen (Digital Phenome), MONet (Molecular Observation Network), and MIDAS (Modeling, Integration, and Data Agents for Science). Due to the centrality of data and computing infrastructure systems in the group’s work, CAM also works closely with the group led by EMSL’s Chief Data Oﬃcer. The CAM group has two teams: Systems Modeling, and Data Transformations.

AI Leadership

Lead the design, development, and sustainment of an ecosystem of AI-powered agents, and necessary infrastructure, to accelerate scientific discovery by automating manual workflows and increasing EMSL’s capacity and efficiency, leveraging frameworks such as Agents SDK, ADK, and LangChain to design, prototype, and develop multi-agent systems capable of semi-autonomous science enhanced with context-aware interactions.
Serve as the focal point for high-priority projects by driving alignment on deliverables, timelines, and resource allocation.
Lead the development of technical roadmaps and implementation strategy in order to drive adoption of emerging AI technologies and best practices.
Drive innovation and agility by integrating the evaluation of new models, frameworks, and approaches into project planning.
Contribute to the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs buy, sustainability vs speed, etc.
Work with multi-disciplinary science teams to identify high-priority opportunities to automate workflows and accelerate scientific discovery, including through the use of low-code/no-code and/or robotic process automation (RPA) platforms.

Technical Leadership

Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions.
Define and maintain standards for model performance, experimentation, testing, deploying, and monitoring, balancing innovation with reliability and stakeholder buy-in.
In collaboration with EMSL’s Computing and Data Operations group, to establish roadmaps for sustainable infrastructure enabling the agentic ecosystem. Examples include multi-site search as well as knowledge curation and management, provenance, prompt management, workflow orchestration, etc.
Lead a small team of scientists and engineers for feature implementation.

Project Leadership

Collaborate with cross-functional teams, including data and computational scientists as well as experimental scientists to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Distill complex research findings and system designs into clear, actionable insights for diverse audiences which include EMSL and PNNL leaders as well as external partners, EMSL users, and sponsors.
Collaborate with UX/UI designers to ensure seamless functionality and intuitive user experiences.
Set and track team goals and metrics.

Team Development

Mentor a diverse team of computing- and data-focused staff on AI-related topics, software, and career development.
Foster a high-performance culture of collaboration, innovation, and delivering AI projects on time and on budget.
Foster a culture of “build-learn-pivot” and customer focus.
Connect with AI researchers and efforts across PNNL to elevate AI best practices across the institution.

Overall

Collaborates with researchers on the development and innovative application of advanced simulation, data analysis, visual analytics, or other computational techniques to research problems in the sciences, engineering, or other disciplines for which computational approaches are significant. May specialize in: Computational Chemistry: Uses computer simulation and develops new algorithms and implementations to investigate chemical systems. Computational Biology: Conducts research using bioinformatics theory and methods in areas such as biotechnology, computational biology, proteomics, computer information science, biology, and medical informatics.

Qualifications

Minimum Qualifications:

BS/BA and 7+ years of relevant experience -OR-
MS/MA and 5+ years of relevant experience -OR-
PhD with 3+ year of relevant experience

Preferred Qualifications

Possesses advanced expertise in developing and deploying autonomous AI systems for practical, real-world applications. Science applications is a plus.
Master-level proficiency in software engineering practices like version control (Git workflows), code reviews, automated testing, CI/CD pipelines, static code analysis, thorough documentation, secure coding, performance optimization, and Agile/DevOps methodologies.
Experience working in large, matrixed organization.
Leading cross-functional teams and mentoring junior staff.
Experience in cloud-native system design, encompassing API development, microservices architecture, containerization (Docker/Kubernetes), infrastructure as code, and comprehensive observability solutions (logging, metrics, tracing).
Highly skilled in Python.
Hands-on experience with leading neural network and deep-learning frameworks such as TensorFlow, PyTorch, or JAX.
Extensive knowledge and practical expertise in modern large language model (LLM) orchestration and agent frameworks, including tools like LangChain and LlamaIndex, along with related open-source software.
Strong grasp of system architecture, distributed computing, and microservices design.
Demonstrated proficiency in deploying applications across major cloud platforms (AWS, Azure, Google Cloud Platform) or secure edge environments.
Experienced in integrating multimodal data formats such as text, images, and structured/sensor data into unified decision-making systems.
Familiarity with cutting-edge generative AI methodologies, including LLM fine-tuning (LoRA/PEFT, QLoRA for SLMs, and dataset preparation), retrieval-augmented generation, prompt engineering, and performance evaluation practices.
Contributions to open-source AI frameworks (e.g., Hugging Face, LangChain, Llama) or publications in respected peer-reviewed journals is a plus.
Strong communication skills in both writing and speaking, with the ability to clearly explain complex concepts to both technical and non-technical audiences.

Hazardous Working Conditions/Environment

Not Applicable

Additional Information

“Referral Eligible”

Testing Designated Position

This is not a Testing Designated Position (TDP).

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.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov.

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 $144,900.00/Yr.

Maximum Salary

USD $229,000.00/Yr.