1

Internship Retrieval Augmented Generation Jobs in California

AI/ML Engineer

Burbank, CA · On-site

$111K - $153K/yr

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows . The ideal candidate will bring deep expertise ...

Senior Agentic AI Engineer

Long Beach, CA · On-site

$114K - $156K/yr

This role focuses on agentic workflows, retrieval-augmented generation (RAG), tool orchestration, evaluation, and production deployment of GenAI systems. You will work at the intersection of LLMs ...

Software Engineer (Java + GenAI)

San Jose, CA · On-site

$60.75 - $83.25/hr

... Retrieval-Augmented Generation (RAG) - Vector databases - Prompt engineering - Large Language Models (LLMs) - Application: Send suitable profiles and contact details to rams@vensoft.com

Advanced AI/ML: Strong expertise in Large Language Models (LLMs), including techniques like prompt engineering and Retrieval-Augmented Generation (RAG) * Coding Excellence: Proficiency in ...

Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities • Applying Machine Learning technologies for anomaly detection Minimum Qualifications Bachelor's degree in ...

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Retrieval-Augmented Generation (RAG) * Feature engineering and model evaluation techniques * Experience working with cloud platforms such as Azure, AWS, or similar ecosystems * Familiarity with data ...

next page

Showing results 1-20

Internship Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as an intern working with Retrieval Augmented Generation (RAG), and why are they important?

To thrive as an intern in Retrieval Augmented Generation, you need a foundational understanding of natural language processing, machine learning concepts, and strong programming skills, often supported by coursework or research in computer science or data science. Familiarity with tools like Python, PyTorch or TensorFlow, and experience with libraries such as Hugging Face Transformers and vector databases are typically required. Strong analytical thinking, curiosity, and effective communication make candidates stand out in collaborative, research-intensive environments. These abilities are critical for developing, evaluating, and improving RAG systems that combine information retrieval with generative models.

What is an Internship in Retrieval Augmented Generation (RAG)?

An Internship in Retrieval Augmented Generation (RAG) is a temporary position, typically for students or early-career professionals, focused on developing or researching AI systems that combine information retrieval with generative models. Interns in this field may work on enhancing how AI models find and use external data sources to generate accurate, context-aware responses. This role often involves tasks such as data preprocessing, implementing retrieval algorithms, fine-tuning language models, and evaluating system performance. It offers valuable hands-on experience with cutting-edge AI technologies and frameworks.

What types of projects or tasks can I expect to work on during an Internship in Retrieval Augmented Generation (RAG)?

As an intern in Retrieval Augmented Generation, you can expect to work on projects that involve integrating information retrieval systems with generative AI models. Typical tasks may include curating and preprocessing data sets, developing or fine-tuning retrieval algorithms, evaluating the performance of RAG pipelines, and collaborating with engineers and researchers to improve end-to-end system accuracy. You may also assist in conducting experiments, analyzing results, and documenting findings, all within a collaborative team environment that values innovation and knowledge sharing.

What is the difference between Internship Retrieval Augmented Generation vs Internship Data Analyst?

AspectInternship Retrieval Augmented GenerationInternship Data Analyst
Required SkillsKnowledge of AI, NLP, retrieval systems, programmingData analysis, statistical skills, Excel, SQL
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Employer UsageDevelop AI models, improve retrieval systemsAnalyze data trends, generate reports

Internship Retrieval Augmented Generation focuses on developing AI models that combine retrieval systems with language generation, requiring skills in AI and programming. In contrast, an Internship Data Analyst concentrates on analyzing data sets to inform business decisions, emphasizing statistical and analytical skills. Both roles are common in tech and business sectors but serve different functions within organizations.

What are the most commonly searched types of Retrieval Augmented Generation jobs in California? The most popular types of Retrieval Augmented Generation jobs in California are:
What are popular job titles related to Internship Retrieval Augmented Generation jobs in California? For Internship Retrieval Augmented Generation jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Retrieval Augmented Generation jobs in California look for? The top searched job categories for Internship Retrieval Augmented Generation jobs in California are:
What cities in California are hiring for Internship Retrieval Augmented Generation jobs? Cities in California with the most Internship Retrieval Augmented Generation job openings:
Infographic showing various Internship Retrieval Augmented Generation job openings in California as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution.

Other

Re-posted 21 days ago


Job description

Lab Summary:AI Research Center (AIC) located in Mountain View, California focuses on research and development which directly impacts future Samsung products reaching hundreds of millions of users worldwide. We are focused on pushing the state-of-the-art and practice in natural language and knowledge intelligence. 

Position Summary: Samsung Research AI center, located in Mountain View, CA, is currently recruiting world-class students who can thrive in a fast-pace, cross team, results-driven environment, with focus on highly visible, challenging, and cross discipline projects. You will be part of an exciting project to build an adaptive, personalized, contextual and secure AI model and system to enable fast, accurate and safe interactions tailored to users' needs on Samsung devices. 

Position Responsibilities: We are looking for Fall Interns (Flexible start date for a 3 month internship between September-December).

  • Develop and implement novel deep learning/reinforcement learning algorithms for natural language processing (text, speech) in various applications 
  • Contribute to the research activities of our team 
  • Generate creative solutions (patents) and publish in top conferences (papers) 

Required Skills: 

  • Current Ph.D. student in CS, EE, or related field 
  • Experience in one or more of the following areas:  
    • Expertise in LLM including model architecture, training/finetuning techniques, retrieval augmented generation (RAG), reasoning and action planning, etc.
    • Experience in planning, tool use, agent AI, and agent memory to develop autonomous systems for decision-making, problem-solving, and adaptability. 
    • Experience in knowledge augmented AI technologies (e.g., language prompt, knowledge graph, neuro-symbolic learning)
    • Experience in conversational AI technologies: natural language processing (e.g., language models, semantic parsing, natural language generation etc.), dialogue (e.g., state tracking, policy learning), and representation learning (embedding, conceptualization, etc.)
    • Experience in multimodal AI technologies for various multimodal applications
    • Experience in on-device AI technologies such as lightweight model architecture design
  • Teamwork and communication skills 
  • Proficiency in a neural network library (e.g., PyTorch, TensorFlow)
  • Track record of research/publications on machine learning and artificial intelligence field (NeurIPS, ICML, ICLR, AAAI, IJCAI, CVPR, ACL, EMNLP, NAACL, TACL, etc.)