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Pacific Northwest National Laboratory

National lab advancing energy, security, environment

Machine Learning Engineer 2

Applied Machine LearningPosted on Nov 9
Full-time$114k - $182.1k /yr

About the Job

Requirements

  • A BS/BA and two years of data science experience, or an MS/MA, or a PhD.
  • 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.
  • U.S. citizenship is required.
  • Applicants must be able to obtain and maintain a federal security clearance and meet eligibility requirements for access to classified matter.
  • Applicants must demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the Questionnaire for National Security Positions.
  • Applicants must pass pre-employment drug testing and are subject to post-employment random drug testing.
  • New employees must successfully complete the applicable tier of federal background investigation and receive a favorable federal adjudication to obtain an HSPD-12 Personal Identity Verification credential.
  • Foreign national candidates who have not resided in the U.S. for three consecutive years are not eligible for the PIV credential and must obtain a favorable Local Site Specific Only federal risk determination to maintain employment.
  • Employees must disclose any affiliation with a government of a DOE-designated country of risk and recuse themselves from that affiliation or receive approval before their first day of employment.

Responsibilities

  • Implement and adapt deep learning and computational methods with researchers, investigating algorithmic assumptions and debugging implementation and model behavior.
  • Independently develop, test, and maintain defined software components or features, making design decisions within the broader architecture.
  • Implement, test, and maintain components of agentic AI workflows, including model tool calling and integration with APIs or data sources, making implementation decisions within the broader software architecture.
  • Build reusable packages, APIs, and interfaces that connect research methods with sponsor systems and workflows.
  • Refactor experimental code and improve its clarity, performance, and maintainability.
  • Develop tests and evaluations that compare implementations with research results and verify behavior as software changes.
  • Use reproducible environments, dependency management, automated testing, and documentation to support collaborative development.
  • Work with other engineers to integrate and deploy components, resolve defects, and incorporate research advances and stakeholder feedback.
  • Coordinate changes in shared codebases, participate in code reviews, and share methods and findings with colleagues.
  • Share implementation approaches and findings with researchers and engineers working in the broader effort.
  • Conduct work in secure environments in accordance with operational security requirements.

Desired Qualifications

  • Experience with modular software design, automated testing, version control, and collaborative development.
  • Experience building or adapting agentic AI applications, including workflow orchestration, tool integration, or tracing and evaluating multi-step behavior.
  • Experience interpreting technical literature or mathematical descriptions and collaborating with researchers to implement methods and evaluate results, particularly in AI Assurance, agentic AI, or applied mathematics.
  • Experience developing reusable packages or APIs and integrating them into larger systems.
  • Experience deploying and maintaining ML or computational software, including reproducible environments, dependency management, automated build and deployment workflows, and incorporating user feedback.
  • Experience supporting national security missions.

About the Company

Pacific Northwest National Laboratory

National lab advancing energy, security, environment

Pacific Northwest National Laboratory (PNNL) conducts scientific research in chemistry, Earth sciences, biology, and data science to advance energy resiliency and national security. Its work spans designing and running experiments, developing models and simulations, and analyzing large data sets to generate knowledge and practical tools that help improve energy systems, environmental stewardship, and security. PNNL differentiates itself through its interdisciplinary approach across multiple scientific domains and its role as a government-funded national lab focused on real-world challenges, enabling collaborations with industry, academia, and government partners. Its goal is to produce actionable scientific insights and deployable technologies that strengthen national resilience and energy infrastructure.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Richland, WA
Founded
1965

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