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Entry Level Large Language Model Llm Jobs in Ohio

Data Scientist

Beavercreek, OH · On-site

$77K - $176K/yr

Experience with engineering AI solutions, including accessing Large Language Model (LLM) APIs, self-hosting LLMs, fine-tuning LLMs, or implementing Model Context Protocol * Experience working with ...

Data Scientist

Dayton, OH · On-site

$77.50 - $176/hr

Experience with engineering AI solutions, including accessing Large Language Model (LLM) APIs, self‑hosting LLMs, fine‑tuning LLMs, or implementing Model Context Protocol * Experience working ...

$102.57 - $136.77/hr

LLM integration & MCP: Practical experience integrating Large Language Models into SaaS products; hands‑on with Model Context Protocol (MCP) server design and implementation * RAG architecture ...

AI Engineer

Cincinnati, OH · On-site +1

$109K - $132K/yr

Research, develop, and implement AI tools such as NLP, LLM, and IA; * Collect, preprocess, and ... Proven experience implementing and fine-tuning Large Language Models or interactive AI applications ...

AI Engineer

Cincinnati, OH · On-site

$109K - $132K/yr

Research, develop, and implement AI tools such as NLP, LLM, and IA; * Collect, preprocess, and ... Proven experience implementing and fine-tuning Large Language Models or interactive AI applications ...

AI Engineer

Cincinnati, OH · On-site

$120 - $180/hr

Research, develop, and implement AI tools such as NLP, LLM, and IA; * Collect, preprocess, and ... Proven experience implementing and fine-tuning Large Language Models or interactive AI applications ...

$80.58 - $103.60/hr

Auf dieser Basis entwickelst du KI-gestützte Lösungen, insbesondere RAG-Systeme, Suchlogiken und Prompting-Ansätze, und bindest Large Language Models sowie KI-Agenten an unsere Datenlandschaft an.

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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 Ohio?

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

What are popular job titles related to Entry Level Large Language Model Llm jobs in Ohio?

For Entry Level Large Language Model Llm jobs in Ohio, the most frequently searched job titles are:

What cities in Ohio are hiring for Entry Level Large Language Model Llm jobs?

Cities in Ohio with the most Entry Level Large Language Model Llm job openings:

Infographic showing various Entry Level Large Language Model Llm job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 90% Full Time, 6% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

AI Engineer

Columbus, OH • On-site

$95 - $130/hr

Other

PTO

This job post has expired today. Applications are no longer accepted.


Job description

We are looking for an AI Engineer to work for our client. The ideal candidate aligns with the responsibilities and qualifications outlined below.

This is an exciting opportunity for a hands-on AI practitioner to help drive the adoption of cutting-edge AI tools and engineering practices within a growing technology team, based in a hybrid role in Columbus, OH.

Responsibilities
  • Design, build, and deploy AI-powered features and tools to improve engineering productivity and product capabilities
  • Leverage AI coding assistants such as GitHub Copilot, Claude, and Cursor to accelerate development workflows
  • Collaborate with engineering teams to integrate AI/LLM-based solutions into existing systems and processes
  • Evaluate and prototype emerging AI tools, models, and frameworks to identify opportunities for adoption
  • Develop and maintain prompt engineering best practices and internal documentation
  • Partner with cross-functional stakeholders to identify use cases where AI can drive efficiency or innovation
  • Monitor the performance, reliability, and output quality of AI-driven tools and systems
  • Stay current on advancements in generative AI and large language models, sharing knowledge with the broader team
  • Troubleshoot and resolve issues related to AI tool integration and performance
Qualifications
  • 2-3 years of demonstrated AI engineering experience
  • Hands‑on experience with AI coding tools such as GitHub Copilot, Claude, and Cursor
  • Strong programming skills in one or more languages (e.g., Python, JavaScript, or similar)
  • Familiarity with large language models (LLMs), prompt engineering, and AI‑assisted development workflows
  • Strong problem-solving skills and ability to quickly learn and evaluate new tools and technologies
  • Excellent communication skills and ability to collaborate across technical and non‑technical teams
  • Comfortable working in a hybrid environment with occasional in‑office collaboration
What Our Client Offers
  • Competitive salary with opportunities for performance‑based bonuses
  • Hybrid work schedule based in Columbus, OH
  • Access to cutting‑edge AI tools and technologies
  • Strong culture of innovation and continuous learning
  • Generous paid time off and flexible scheduling
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