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Entry Level Large Language Model Llm Jobs in Pennsylvania

Gap International

AI/LLM Engineer

Springfield, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ... Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges ...

Gap International

AI/LLM Engineer

Philadelphia, PA

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ... Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges ...

The Pennsylvania State University

$19 - $26/hr

The successful candidates will assist in developing large language model (LLM) applications for social science research and data analysis . Preferred qualifications include: * Prior experience ...

The Pennsylvania State University

The research assistant will assist Rock Ethics Institute faculty in a study examining how large-language model (LLM)-controlled artificial agents use and develop social strategies, and ways to foster ...

Tata Consultancy Service Limited

Engineer

Pittsburgh, PA · On-site

$100K - $105K/yr

LLM Basics * RAG * Systems Design and Engineering * Ability to design a fault tolerant production ... Highly skilled Senior Full-Stack Engineer with strong expertise in Python, Large Language Models ...

Gehc

AI Scientist

North East, PA · On-site

Publications as first author on LLM, Agentic AI or self supervised learning (SSL). * Demonstrated ... large language models, etc.) * Track record in developing machine learning solutions using massive ...

RELX Group plc

Senior Data Scientist

Philadelphia, PA · On-site

... large language models, retrieval systems, knowledge graphs, and generative AI to help researchers ... Build and optimize LLM-powered applications, including question answering, literature summarization ...

Elsevier

Senior Data Scientist

Philadelphia, PA · On-site

... large language models, retrieval systems, knowledge graphs, and generative AI to help researchers ... Build and optimize LLM-powered applications, including question answering, literature summarization ...

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Entry Level Large Language Model Llm information

What is an entry level large language model LLM?

An Entry Level Large Language Model (LLM) role typically refers to positions where individuals work with advanced AI systems, like ChatGPT or similar models, to support tasks such as data annotation, model evaluation, prompt engineering, or customer support. Entry-level LLM professionals might help train models, test outputs for accuracy, or assist with basic research. These roles usually require strong analytical skills, attention to detail, and some familiarity with AI concepts, but do not always require advanced programming experience. They offer a great starting point for those interested in the field of artificial intelligence and natural language processing.

What types of projects do entry level large language model LLM engineers typically contribute to?

Entry-level professionals in LLM roles often support data preparation, model fine-tuning, and evaluation tasks under the guidance of more experienced engineers or data scientists. They may annotate data, help run experiments, monitor model outputs for quality, and assist in deploying models for internal testing or limited production use. Collaboration with cross-functional teams—including machine learning engineers, product managers, and research scientists—is common, offering valuable exposure to various stages of the LLM development lifecycle. This hands-on experience helps build foundational skills and prepares individuals for more advanced responsibilities in the field.

What are the key skills and qualifications needed to thrive as an entry level large language model LLM engineer?

To thrive as an Entry Level Large Language Model (LLM) Engineer, you need a solid background in computer science, machine learning fundamentals, and proficiency in programming languages like Python, typically supported by a relevant degree. Familiarity with machine learning frameworks (such as PyTorch or TensorFlow), version control systems, and cloud computing platforms is often required. Strong analytical thinking, problem-solving skills, and effective communication set candidates apart in this role. These competencies are crucial for developing, fine-tuning, and deploying LLMs to ensure innovative and reliable AI solutions.

What is the difference between Entry Level Large Language Model Llm vs Data Analyst?

AspectEntry Level Large Language Model LlmData Analyst
Required CredentialsBasic understanding of NLP, programming skills (Python), coursework or certifications in AI/MLBachelor's degree in Data Science, Statistics, or related field; often certifications in data analysis tools
Work EnvironmentResearch labs, AI companies, tech startups; focus on model development and trainingBusiness environments, consulting firms, finance, healthcare; focus on data interpretation and reporting
Industry UsageAI development, NLP applications, machine learning researchBusiness intelligence, market analysis, operational insights

Entry Level Large Language Model Llm roles focus on developing and training NLP models, requiring programming and AI knowledge. Data Analysts interpret data to inform business decisions, often using statistical tools. While both roles involve working with data, Llm positions are more technical and research-oriented, whereas Data Analysts focus on data interpretation and reporting.

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

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

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Entry Level Large Language Model Llm jobs near you
Infographic showing various Entry Level Large Language Model Llm job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 2% Contract, and 1% Nights. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Software Developer / Engineer - Philadelphia, PA (Locals Only)

Philadelphia, PA • On-site

Apetan Consulting llc
IT Services • 1 - 10 employees
Learn more about Apetan Consulting llcexternal

$80 - $150/hr

Contractor

Re-posted 9 days ago

Job description

Software Developer / Engineer
Location: Philadelphia, PA 
Work Schedule: Hybrid 3 days on site, 2 remote


Position Overview

We are seeking a Software Developer / Engineer to help design and implement an on-premises Large Language Model (LLM) platform with Retrieval-Augmented Generation (RAG) capabilities. This role will focus on deploying open-source AI models, integrating vector databases, and building secure, enterprise-grade AI solutions in a private environment.

This is an excellent opportunity for a developer with hands-on experience in modern AI technologies who enjoys building scalable, high-performance systems.

Responsibilities

  • Deploy and optimize open-source large language models (LLMs) such as Meta Llama 3 and Mistral/Mixtral in on-premises or private environments.
  • Develop Python-based applications for LLM inference, prompt engineering, and model integration.
  • Optimize CPU-based model inference through quantization and performance tuning.
  • Design and implement Retrieval-Augmented Generation (RAG) (RAG) pipelines.
  • Configure and manage open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Generate and manage embeddings while implementing metadata filtering strategies.
  • Support enterprise security requirements, including air-gapped deployments, access controls, data privacy, and audit logging.
  • Produce technical documentation, deployment guidance, and knowledge transfer materials for internal teams.
  • Build a working prototype integrating an LLM, vector database, and RAG architecture.

Required Qualifications

  • Professional experience deploying open-source LLMs (e.g., Meta Llama 3, Mistral/Mixtral) in on-premises or private environments.
  • Strong Python development experience.
  • Hands-on experience with LLM inference, prompt engineering, and AI application integration.
  • Experience optimizing CPU-based inference through model quantization and performance tuning.
  • Experience with vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Proven experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Understanding of enterprise security, data privacy, air-gapped environments, access controls, and audit logging.

Preferred Qualifications

  • Experience with LangChain or LlamaIndex.
  • Familiarity with Docker and Kubernetes.
  • Experience with inference frameworks such as vLLM, llama.cpp, or Hugging Face Transformers.
  • Experience with Rust, Go, or C++.
  • Previous experience working in enterprise or regulated environments.

Deliverables

  • Reference architecture and deployment guidance.
  • Working prototype integrating an LLM, vector database, and RAG solution.
  • Technical documentation and knowledge transfer to internal teams.