Summer DevOps Internship — Hybrid, Cloud & CI/CD

Lawrence Livermore National Laboratory

Livermore (CA)

Hybrid

USD 66,650,000 - 95,647,000

Full time

5 days ago
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Benefits offered by this job

Holiday Pay
Sick leave accrual
Individual 401(k) contributions

Job summary

Lawrence Livermore National Laboratory invites undergraduates in CS, Math, Data Science, ML, or related STEM fields to join the Summer DevOps Internship Program. You will engage in practical research, supporting containerization, CI/CD automation, cloud-native deployments, and production software operations.

Hybrid schedule with potential work-from-home days; you may contribute to large language model deployments, infrastructure automation, and platform engineering projects alongside experienced

Qualifications

  • Eligible to access LLNL per NDAA Section 3112.
  • Enrolled as an undergraduate in a STEM field (CS/Math/Data Science/ML/Cybersecurity).
  • GPA of 3.0 or higher.
  • Strong communication and teamwork skills.
  • Able to work in a lab environment and follow safety protocols.

Responsibilities

  • Learn Git, containerization, CI/CD, and Kubernetes deployment.
  • Contribute to DevOps and platform engineering projects (web services, automation, production ops).
  • Assist in deploying and testing large language models and data services.
  • Develop automation tools, deployment workflows, monitoring, and docs.
  • Participate in code reviews, testing, and lifecycle activities.
  • Engage in research planning and evaluation discussions.
  • Attend seminars weekly and present work via talks or posters.

Skills

Adaptability
Communication
Teamwork
Problem-solving
Public speaking

Education

Undergraduate in CS/Math/Data Science/ML/Cybersecurity

Tools

Git
Docker
Kubernetes

Job description

Lawrence Livermore National Laboratory invites undergraduates in CS, Math, Data Science, ML, or related STEM fields to join the Summer DevOps Internship Program. You will engage in practical research, supporting containerization, CI/CD automation, cloud-native deployments, and production software operations.

Hybrid schedule with potential work-from-home days; you may contribute to large language model deployments, infrastructure automation, and platform engineering projects alongside experienced

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