Machine Learning Engineer

$132,810 - $170,556/Yr

Lawrence Livermore National Laboratory - Livermore, CA

Full-time - Mid Level

Livermore, CA

Professional, Scientific, and Technical Services

About the position

The Machine Learning Engineer position at Lawrence Livermore National Laboratory (LLNL) involves collaborating with research software teams to develop and maintain machine learning infrastructure and software across various application domains. The role requires applying software development and machine learning knowledge to contribute to multiple projects, focusing on enhancing the laboratory's mission in national security and scientific research. The position is available at two levels (SES.2 and SES.3), with responsibilities increasing at the higher level.

Responsibilities

• Develop and maintain common infrastructure for machine learning library deployments and continuous integration.
• Perform machine learning software development tasks across various application domains.
• Assist in modernizing and deploying machine learning libraries and workflows on high-performance computing systems and cloud platforms.
• Help develop, test, and apply machine learning algorithms and pipelines to scientific applications.
• Contribute to technical projects and organizational objectives as a team member.
• Engage with other developers to share knowledge and recommendations.
• Manage multiple advanced parallel tasks and priorities at the SES.3 level.

Requirements

• Ability to obtain and maintain a US DOE Q-level security clearance requiring U.S. Citizenship.
• Master's degree in Computer Science, Computer Engineering, or related field, or equivalent experience.
• Proficiency in a modern programming language such as C++ or Python.
• Experience deploying machine learning pipelines in production.
• Experience developing software on Linux HPC clusters or similar environments.
• Ability to work with limited direction on technical tasks and develop solutions.
• Proficient verbal and written communication skills for collaboration and reporting.

Nice-to-haves

• Experience developing and deploying containers to local and cloud environments.
• Experience with continuous integration, testing, and automated workflows.
• Experience with build systems such as CMake and software packaging.

Benefits

• 401(k)
• Flexible schedule
• Relocation assistance
• Tuition reimbursement