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Intern Llm Developer Jobs in California (NOW HIRING)

Workato

Intern, AI Engineering

San Francisco, CA

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas ... LLM Agent Systems : Design and implement intelligent agent architectures for complex enterprise ...

Workato

Intern, AI Engineering

San Francisco, CA · On-site

$19.75 - $25.50/hr

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas ... LLM Agent Systems : Design and implement intelligent agent architectures for complex enterprise ...

Workato

Intern, AI Engineering

San Francisco, CA · On-site

$19.75 - $25.50/hr

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas ... LLM Agent Systems : Design and implement intelligent agent architectures for complex enterprise ...

Fluency

Engineering Intern

San Francisco, CA · On-site

$20/hr

About the internship We're hiring an Engineering Intern for a 13-week internship at our San ... LLM data pipelines, agent orchestration, observability, and the tooling other engineers rely on.

MaxLinear, Inc.

AI Intern

Carlsbad, CA

$25 - $40/hr

LLM inference, MCP integration, Robot Framework, Python, and the Jira / Bitbucket / Confluence ... Bachelors of Science, Computer Science, Engineering or similar in progress; Masters student ...

Fujitsu

Agentic AI Research Intern

Santa Clara, CA · On-site

$40 - $50/hr

We are seeking a highly motivated PhD intern to work on LLM-based agents for end-to-end software ... The intern will collaborate with AI researchers and engineers to develop agent systems that can ...

Etched

DV Intern

San Jose, CA · On-site

Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is ... Familiarity with modern ML and LLM model architectures * UVM or formal verification experience

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Intern Llm Developer information

What are the key skills and qualifications needed to thrive as an Intern LLM Developer, and why are they important?

To thrive as an Intern LLM Developer, you generally need a solid background in computer science, programming (especially Python), and foundational knowledge of machine learning concepts. Familiarity with deep learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and exposure to large language models (LLMs) are typically required. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate and learn in dynamic team environments. These skills and qualities are vital for contributing to cutting-edge AI projects and rapidly adapting to evolving technologies in the field.

What does an Intern LLM Developer do?

An Intern LLM (Large Language Model) Developer supports the development, testing, and deployment of AI models, specifically large language models like GPT or BERT. Their responsibilities often include data preprocessing, model fine-tuning, writing code to interact with APIs, and evaluating model performance. Interns work under the guidance of senior developers and researchers to gain hands-on experience in natural language processing and AI. This role is ideal for students or recent graduates looking to build practical skills in machine learning and AI development.

What types of projects and learning opportunities can an Intern LLM Developer expect to work on during their internship?

As an Intern LLM Developer, you can expect to participate in hands-on projects involving the development, fine-tuning, or evaluation of large language models (LLMs). Typical responsibilities include data preprocessing, implementing model training pipelines, and collaborating with senior engineers and data scientists to optimize model performance. You'll also have opportunities to contribute to research on natural language processing (NLP) tasks and gain exposure to industry-standard tools and frameworks. This role offers valuable mentorship and the chance to build practical skills in machine learning and AI, setting a strong foundation for a future career in the field.

What is the difference between Intern Llm Developer vs Intern Machine Learning Engineer?

AspectIntern Llm DeveloperIntern Machine Learning Engineer
Required CredentialsTypically pursuing or recent graduate in Computer Science, AI, or related fieldsSimilar educational background, often with focus on ML or AI
Work EnvironmentTech companies, AI startups, research labsTech firms, startups, research institutions
Employer & Industry UsageFocused on developing large language models and NLP applicationsDeveloping various ML models, including NLP, computer vision, etc.
Common Search & ComparisonIntern Llm Developer vs Intern Machine Learning Engineer

Intern Llm Developers primarily focus on building and fine-tuning large language models, often specializing in NLP tasks. Intern Machine Learning Engineers have a broader scope, working on various ML models across different domains. Both roles require similar educational backgrounds and are found in tech and AI industries, but their specific focus areas differ.

What are the most commonly searched types of Llm Developer jobs in California? The most popular types of Llm Developer jobs in California are:
What are popular job titles related to Intern Llm Developer jobs in California? For Intern Llm Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Intern Llm Developer jobs in California look for? The top searched job categories for Intern Llm Developer jobs in California are:
What cities in California are hiring for Intern Llm Developer jobs? Cities in California with the most Intern Llm Developer job openings:
Intern Llm Developer jobs near you

Intern, AI Engineering

Workato

San Francisco, CA

Other

Re-posted 24 days ago

Job description

Workato AI LabAbout Workato AI Lab

Workato AI Lab is at the forefront of enterprise AI innovation, developing cutting-edge agentic systems that transform how businesses automate and optimize their workflows. Our team bridges academic research with real-world applications, creating AI systems that serve millions of users across global enterprises.

Responsibilities

We are seeking exceptional graduate students to join our AI Lab as Research Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and efficient AI infrastructure, with opportunities to publish your research while making direct impact on production systems serving enterprise customers.
We are now filling intern positions for Winter 2026 and Spring 2027. 

Research Areas

  • LLM Agent Systems: Design and implement intelligent agent architectures for complex enterprise automation tasks, including multi-agent collaboration, MCP, and reasoning frameworks

  • Efficient LLM Fine-tuning: Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for large language models

  • High-Performance LLM Inference: Optimize inference pipelines through systems-level innovations, kernel development, and deployment strategies

In this role, you will also be responsible to:

  • Conduct original research on LLM agent architectures and optimization techniques

  • Develop and evaluate novel algorithms with both academic rigor and production feasibility

  • Present your work at internal research seminars and external conferences

  • Mentor and collaborate with LLM  engineers on implementation and deployment

RequirementsQualifications / Experience / Technical Skills

  • Currently pursuing MS/PhD in Computer Science, Machine Learning, Natural Language Processing, or related fields

  • Publications at top-tier venues (ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL)

  • Strong programming skills in Python and PyTorch

  • Ability to work in-person at our San Francisco office

  • Ability to work independently and collaborate across research and engineering teams

Preferred:

  • Experience with self-evolving agent systems

  • Proficiency in CUDA programming and custom kernel development for LLM operations

  • Background in reinforcement learning-based LLM fine-tuning 

  • Track record of contributions to production inference systems such as vLLM, TensorRT-LLM, SGLang, or Hugging Face ecosystem

  • Experience bridging academic research with production systems

  • Open-source contributions to widely-used ML infrastructure projects

(REQ ID: 2690)

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