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Lawrence Livermore National Laboratory (LLNL)

National security research laboratory

Data Science Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLivermore, CA, USA

About the Job

Requirements

  • Ability to secure and maintain a U.S. Department of Energy Q-level security clearance, which requires U.S. citizenship.
  • A bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field, or an equivalent combination of education and related experience.
  • Broad experience with Python programming and software development.
  • Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems.
  • Intermediate knowledge of software engineering best practices, including version control, unit testing, and documentation.
  • Verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences.
  • Interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment.
  • Ability to balance multiple projects and prioritize competing demands while maintaining high-quality standards for deliverables.
  • At the SES.3 level, advanced experience in applied machine learning and data science, with the ability to deliver complex technical solutions independently.
  • At the SES.3 level, advanced experience building innovative data science systems and discovering novel approaches to complex problems.
  • At the SES.3 level, experience presenting technical work and demonstrations to technical and non-technical audiences, including sponsors and stakeholders.

Responsibilities

  • Design, develop, and apply machine learning and data science algorithms, including deep learning and modern artificial intelligence techniques such as neural networks, transformers, and generative models, to analyze cybersecurity and power systems data.
  • Analyze data and build analytical capabilities to improve the reliability and adversarial resilience of critical infrastructure.
  • Write code to implement and deploy data science solutions and analytical tools, create visualizations, and follow software engineering best practices for code quality, testing, and documentation.
  • Collaborate with multidisciplinary teams, including cybersecurity experts, power systems engineers, and computer scientists.
  • Support the development of research prototypes and capabilities for critical infrastructure protection, contributing to new methodologies and tools.
  • Provide solutions to moderately complex to complex data analytics challenges in cybersecurity and power systems using established and innovative methods.
  • Perform other duties as assigned.
  • At the SES.3 level, lead highly complex projects with technical and analytic challenges, developing innovative solutions and building advanced capabilities.
  • At the SES.3 level, discover and pioneer new approaches to data science problems, advancing current methodologies and transforming ideas from concepts into operational solutions.
  • At the SES.3 level, regularly present technical work and results to sponsors and technical audiences through hands-on demonstrations and in-depth technical discussions.
  • At the SES.3 level, contribute to technical direction and strategy for data science capabilities in critical infrastructure protection by building proof-of-concept systems, demonstrating new approaches, and contributing ideas to research proposals.

Desired Qualifications

  • A master's degree or PhD in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field.
  • Experience with modern machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, or similar tools.
  • Experience with deep learning techniques, transformer models, retrieval-augmented generation, fine-tuning pretrained models, or adapting foundation models for specific application domains.
  • Knowledge of cybersecurity principles and practices, including threat detection, anomaly detection, or security analytics.
  • Experience with power systems, supervisory control and data acquisition systems, industrial control systems, or operational technology environments.
  • Experience with data visualization and effectively communicating analytical results to diverse audiences.

About the Company

Lawrence Livermore National Laboratory (LLNL)

National security research laboratory

LLNL conducts scientific and technological research funded by the U.S. government to address national security, energy, and environmental challenges. Its multidisciplinary teams create technologies through projects funded by contracts and grants, delivering outputs such as advanced materials, simulations, software, and vaccines. Unlike private vendors, LLNL operates as a national laboratory with access to unique facilities and mission-driven funding, collaborating with government, universities, and industry. Its goal is to apply science and engineering to protect people, improve energy and environmental sustainability, and advance national security and public welfare.

Company size
5,001-10,000
Company stage
Grant
Total funding
$7.8M
Headquarters
Livermore, CA
Founded
1952

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