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Gpt Jobs in Wisconsin (NOW HIRING)

Devitechs

WI · On-site

$80 - $120/hr

Design and develop end-to-end LLM-powered applications using GPT-4, GPT-5 or custom models. * Integrate ChatGPT with backend systems through REST APIs, WebSockets, and cloud functions. * Build ...

BioVille

WI · On-site

$68.51 - $102.76/hr

Claude skills, plugins, MCP-servers, GPT's of custom AI-tools. Je weet hoe die technologie onder de motorkap werkt en je hebt ideeën te over over hoe AI het werk binnen bedrijven kan vereenvoudigen.

Gainwell Technologies

WI · On-site

$147.20 - $210.30/hr

Experience developing, deploying, and finetuning LLMs (GPT, Gemini, Claude or similar) for real-world applications including prompt engineering, model optimization and inference efficiency. * Strong ...

Jobtailor

WI · On-site

$80 - $120/hr

Fluency with modern AI tooling (Claude, GPT/Codex, MCP servers, AI agents) and experience embedding AI-assisted workflows into analytics work. * Knowledge of engineering productivity metrics -- DORA ...

Directsupply

Senior Digital Workplace Engineer

Milwaukee, WI · Hybrid

$103K - $141K/yr

Demonstrated experience deploying AI-enhanced collaboration tools (e.g., Microsoft Copilot, GPT integrations). * Deep expertise in the Microsoft 365 ecosystem, including Entitlement Management, Teams ...

Ernst & Young Advisory Services Sdn Bhd

WI · On-site

$90 - $130/hr

GPT, Mistral, Azure, CoPilot, Snowflake, Databricks, ...; * AI-Driven Innovation:Explore cutting‑edge technologies like Machine Learning, Deep Learning, and GenAI to revolutionize entire ...

Dataroots BVBA

WI · On-site

$110 - $170/hr

You know the model landscape (Claude, GPT, Gemini, open-weight models) well enough to reason about trade-offs: capability, cost, and latency. * You take governance and security seriously: auth, data ...

Johnson Controls

Ai Engineer

Milwaukee, WI · On-site

Develop and deploy Generative AI systems and LLM-powered applications (e.g., GPT, Claude, LLaMA) for use cases such as enterprise search, document summarization, and conversational AI. * Apply prompt ...

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All JobsGpt JobsGpt Jobs in Wisconsin

Gpt information

See Wisconsin salary details

$38.6K

$146.9K

$215.3K

How much do gpt jobs pay per year?

As of Aug 29, 2026, the average yearly pay for gpt in Wisconsin is $146,948.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,200.00 and $195,200.00 per year, depending on experience, location, and employer.

What is a GPT?

A GPT job typically refers to a role related to Generative Pre-trained Transformers (GPT), which are AI models designed for natural language processing tasks. These jobs can involve developing, fine-tuning, or applying GPT models in areas like content generation, customer support automation, and AI research. Positions may include machine learning engineers, NLP researchers, or prompt engineers, depending on the specific application of GPT technology.

What are the key skills and qualifications needed to thrive as a GPT engineer, and why are they important?

To thrive as a GPT engineer, you need a strong background in machine learning, natural language processing, and programming languages such as Python, typically supported by a degree in computer science or a related field. Proficiency with deep learning frameworks (like TensorFlow or PyTorch), cloud platforms (such as AWS or Google Cloud), and experience with large language models are crucial. Strong analytical thinking, creativity, and collaborative communication are soft skills that set top performers apart in this field. These skills and qualities are vital to effectively develop, fine-tune, and deploy advanced AI language models that meet real-world applications and ethical standards.

What are some common challenges faced by professionals working as GPT engineers, and how can they overcome them?

GPT engineers often encounter challenges such as fine-tuning models for specific tasks, managing large-scale datasets, and optimizing computational resources. They may also need to address ethical concerns and mitigate biases in generated outputs. To overcome these obstacles, engineers typically collaborate closely with data scientists, ethicists, and DevOps teams, and stay updated with the latest research and best practices in the field. Continuous learning and leveraging open-source tools can also help tackle evolving technical and ethical challenges.

What is the difference between Gpt vs Chatbot Developer?

AspectGptChatbot Developer
Required CredentialsKnowledge of AI, NLP, programming skillsProgramming, AI, UI/UX design
Work EnvironmentAI research labs, tech companiesSoftware companies, customer service teams
Industry UsageAI language models, automationCustomer support, interactive bots
Common Search IntentUnderstanding AI models like GptBuilding or improving chatbots

Gpt refers to advanced AI language models like OpenAI's GPT, focusing on natural language understanding and generation. Chatbot Developers design and implement chatbots, often utilizing models like Gpt. While Gpt is a technology, Chatbot Developers apply such technologies to create interactive applications. Both roles overlap in AI and programming skills but differ in focus: Gpt is a model, whereas Chatbot Developers build user-facing solutions.

What are popular job titles related to Gpt jobs in Wisconsin?

For Gpt jobs in Wisconsin, the most frequently searched job titles are:

Gpt jobs near you
Infographic showing various Gpt job openings in Wisconsin as of August 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $146,948 per year, or $70.6 per hour.

LLM (ChatGPT) Application Engineer

Devitechs

WI • On-site

$80 - $120/hr

Other

Posted 11 days ago

Job description

Responsibilities
  • Design and develop end-to-end LLM-powered applications using GPT-4, GPT-5 or custom models.
  • Integrate ChatGPT with backend systems through REST APIs, WebSockets, and cloud functions.
  • Build scalable AI pipelines for summarization, content generation, Q&A, and automation tasks.
  • Fine-tune models using available datasets to improve accuracy for specific business domains.
  • Implement guardrails, moderation rules, and safety filters to control model output.
  • Build vector search systems using FAISS, Pinecone, Weaviate, or Milvus.
  • Work with RAG (Retrieval Augmented Generation) frameworks for grounded responses.
  • Implement caching, batching, and optimization for cost reduction and performance.
  • Develop structured workflows for approvals, escalations, and error handling in LLM interactions.
  • Monitor LLM performance through logs, metrics, and analytics dashboards.
  • Test model outputs for correctness, consistency, and hallucination risks.
  • Collaborate with product and design teams to create LLM-driven UX flows.
  • Maintain secure handling of sensitive data used in model queries.
  • Implement multi-agent systems for complex AI interactions and decision-making.
  • Automate repetitive business tasks using ChatGPT-powered agents.
  • Document data flows, architecture, model behaviors, and system dependencies.
  • Troubleshoot model-related issues including context loss and misclassification.
  • Scale LLM applications using Kubernetes, serverless functions, and cloud orchestration.
  • Stay updated with the latest GPT model releases, research papers, and API features.
  • Provide internal training on LLM capabilities, limitations, and best practices.
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