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Internship Large Language Model Llm Jobs in Texas

Experience with fine-tuning Large Language Models (LLM) on external datasets. * Hands-on experience with using HuggingFace APIs. * 4 Years Experience with Python and 2 Years of Professional ...

Experience with fine-tuning Large Language Models (LLM) on external datasets. * Hands-on experience with using HuggingFace APIs. * 4 Years Experience with Python and 2 Years of Professional ...

Senior AI Language Model Engineer

Houston, TX · On-site

$99K - $137K/yr

Strong foundation in large language models (LLMs) and natural language processing (NLP), with ... Familiarity with modern NLP/LLM frameworks and libraries such as LangChain, LangGraph, Hugging Face ...

Applied Scientist

Austin, TX · On-site

$170 - $230/hr

Experience with fine-tuning Large Language Models (LLM) on external datasets. * Hands-on experience with using HuggingFace APIs. * 4 Years Experience with Python and 2 Years of Professional ...

Strong foundation in large language models (LLMs) and natural language processing (NLP), with ... Familiarity with modern NLP/LLM frameworks and libraries such as LangChain, LangGraph, Hugging Face ...

Software Engineer - Advanced

Plano, TX · On-site

$90 - $95/hr

About the Role We are seeking a Senior AI/ML Full Stack Engineer to design and deliver production-grade intelligent applications powered by modern AI/ML and large language model (LLM) technologies.

You will have the opportunity to acquire a broad spectrum of knowledge spanning various disciplines and stages of silicon design, also applying machine learning (ML) and large language modeling (LLM ...

Showing results 21-40

Internship Large Language Model Llm information

What is an internship in large language model (LLM)?

An Internship in Large Language Model (LLM) typically involves working with advanced artificial intelligence models like GPT or similar technologies. Interns in this field assist with tasks such as data preparation, model training, evaluation, and deployment of natural language processing applications. They may also contribute to research, experimentation, and development of new model features or performance improvements. This role provides hands-on experience in AI, machine learning, and natural language processing, often requiring knowledge of programming, data science, and AI concepts.

What types of projects do interns typically work on during a large language model (LLM) internship?

During a Large Language Model (LLM) internship, interns often participate in projects such as data preprocessing, fine-tuning models on specific tasks, evaluating model outputs, and developing tools for model interpretability. Interns may collaborate closely with research scientists and engineers, contributing to both experimental and production-level code. These projects provide practical experience with natural language processing pipelines and exposure to the latest advancements in AI, making it a valuable learning opportunity for those interested in a career in machine learning and artificial intelligence.

What are the key skills and qualifications needed to thrive as an internship large language model (LLM) specialist?

To thrive as an Internship Large Language Model (LLM) specialist, you need a solid grasp of machine learning fundamentals, natural language processing, and proficiency in programming languages like Python, often supported by coursework or research in computer science or related fields. Familiarity with tools such as TensorFlow, PyTorch, Hugging Face Transformers, and experience using cloud platforms are typically required. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate with teams and present complex ideas clearly. These competencies are crucial for developing, evaluating, and refining LLMs to create impactful AI solutions.

What is the difference between Internship Large Language Model Llm vs Data Scientist Intern?

AspectInternship Large Language Model LlmData Scientist Intern
Required CredentialsRelevant coursework, programming skills, knowledge of NLPStatistics, programming, data analysis
Work EnvironmentAI research labs, tech companies, startupsData analysis teams, tech firms, research institutions
Employer & Industry UsageAI development, NLP projects, machine learningData analysis, predictive modeling, business insights

Both roles involve data and programming skills, but Internship Large Language Model Llm focuses on natural language processing and AI model development, while Data Scientist Interns work on analyzing data to generate insights. The choice depends on your interest in AI/NLP versus data analysis and business applications.

What are the most commonly searched types of Large Language Model Llm jobs in Texas?

The most popular types of Large Language Model Llm jobs in Texas are:

What job categories do people searching Internship Large Language Model Llm jobs in Texas look for?

The top searched job categories for Internship Large Language Model Llm jobs in Texas are:

What cities in Texas are hiring for Internship Large Language Model Llm jobs?

Cities in Texas with the most Internship Large Language Model Llm job openings:

Senior Azure Generative AI Engineer

@Orchard

Dallas, TX

$95/hr

Full-time

Re-posted 20 hours ago


Job description

Senior Azure Generative AI Engineer

Dallas TX

@Orchard LLC is seeking a Senior Azure Generative AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions using Microsoft Azure. This role will focus on building scalable AI applications leveraging Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, Azure Cognitive Services, and modern data engineering practices. As the Senior Gen AI Engineer, you will work closely with business stakeholders, architects, and engineering teams to deliver AI-powered solutions for enterprise and banking use cases.
Your duties and responsibilities:

  • Design, develop, and deploy enterprise Generative AI solutions using Microsoft Azure AI services.
  • Build AI-powered applications utilizing Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, and Azure Cognitive Services.
  • Design and implement Retrieval Augmented Generation (RAG) solutions using Azure AI Search and vector databases.
  • Develop scalable data ingestion, transformation, and preprocessing pipelines to support AI model training and inference.
  • Fine-tune, evaluate, and optimize Large Language Models (LLMs) for enterprise-specific use cases.
  • Collaborate with solution architects, data engineers, and business stakeholders to define AI solution architectures and implementation strategies.
  • Integrate AI services into enterprise applications using REST APIs, Python, and Azure cloud services.
  • Implement MLOps and LLMOps best practices for model deployment, monitoring, governance, and lifecycle management.
  • Ensure AI solutions comply with enterprise security, responsible AI, and regulatory requirements, particularly within the banking and financial services domain.
  • Troubleshoot production AI solutions and continuously improve model accuracy, performance, scalability, and cost optimization.
  • Stay current with emerging Azure AI capabilities and recommend innovative approaches to improve business outcomes.

Required qualifications to be successful in this role:

  • Minimum 6+ years of software engineering, data engineering, or AI/ML development experience.
  • Minimum 3+ years of hands-on experience developing solutions on Microsoft Azure.
  • Minimum 2+ years of hands-on experience building Generative AI or Large Language Model (LLM) applications.
  • Experience delivering enterprise cloud solutions within regulated industries such as banking or financial services is highly preferred.
  • Technical Skills
    • Strong experience with Azure OpenAI Service. 
    • Hands-on experience with Azure AI Foundry (formerly Azure AI Studio).
    • Experience with Azure Machine Learning and Azure Cognitive Services.
    • Strong understanding of Retrieval Augmented Generation (RAG) architecture.
    • Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, or similar technologies.
    • Strong Python programming skills.
    • Experience with LangChain, LangGraph, Semantic Kernel, or similar GenAI orchestration frameworks.
    • Experience with PyTorch, Hugging Face Transformers, or similar ML frameworks.
    • Experience building scalable data pipelines using Azure Data Factory, Synapse, Microsoft Fabric, Databricks, or Spark.
    • Understanding of prompt engineering, model evaluation, fine-tuning, embeddings, and LLM optimization.
    • Experience with CI/CD pipelines and MLOps/LLMOps practices.
    • Familiarity with Git, Azure DevOps, and container technologies (Docker/Kubernetes) is preferred. 
    • Strong understanding of AI governance, responsible AI, and model security.

Compensation: Compensation ranges are determined by several factors, including skill set, experience, licensure and certifications, and location. The anticipated range for a base salary for this role is between $95-115K. There may be some flexibility for exceptionally qualified individuals.

Established in 2010, @Orchard LLC has an exceptional reputation, providing staffing solutions to time-sensitive, talent-scarcity issues to deliver better talent management ROI.  Our specialty lies in the critical area of program talent acquisition and resource management, not in one narrow skillset, but across many areas of technical and functional delivery. To learn more about our other exciting opportunities, visit our Jobs Page at www.atOrchard.com.