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Entry Level Large Language Model Llm Jobs in Virginia

Design and implement Large Language Model (LLM) solutions, Retrieval-Augmented Generation (RAG) architectures, vector databases, and AI-enabled knowledge management capabilities. * Develop scalable ...

Software Developer SME

Chantilly, VA · On-site

$154K - $278K/yr

Develop Java and/or Python applications that leverages Large Language Model (LLM) API calls * Utilized Scrum agile techniques to manage workload and incrementally build out applications to meet ...

Develop Java and/or Python applications that leverages Large Language Model (LLM) API calls * Utilized Scrum agile techniques to manage workload and incrementally build out applications to meet ...

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Entry Level Large Language Model Llm information

What is an Entry Level Large Language Model (LLM) role?

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 are the key skills and qualifications needed to thrive as an Entry Level Large Language Model (LLM) Engineer, and why are they important?

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 types of projects do entry-level professionals working with Large Language Models (LLMs) 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 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.

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Machine Learning Engineer/Data Scientist with Security Clearance

Machine Learning Engineer/Data Scientist with Security Clearance

Avid Technology Professionals

Chantilly, VA • On-site

Other

Re-posted 5 days ago


Job description

Come join an exciting new project utilizing cutting edge technologies in Chantilly, Virginia. Skill-sets: Python, Databricks, LLM (Large Language Model), NLP (Natural Language Processing), model tuning, containerization (Docker/Kubernetes), model validation / testing, prompt engineering, scaling /optimization techniques, software development, and Apache Spark.