1

Llm Jobs in Wisconsin (NOW HIRING)

WI · On-site

$140 - $210/hr

Continuous LLM Evaluation: Design and operate a systematic, ongoing process to evaluate new and emerging LLMs across accuracy, relevancy, speed, and cost -- continuously benchmarking them against the ...

Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem. 520 - 560 a day Rahmenbedingungen Start: Marz/April ...

WI · On-site

$120 - $190/hr

Build and deploy LLM-powered applications, RAG pipelines, and AI agents using Python. * Implement retrieval-augmented generation systems: chunking, embeddings, vector search, hybrid retrieval, and re ...

New

WI · On-site

$62.80 - $85.64/hr

Ontwikkelen van oplossingen op basis van Large Language Models (LLM's) en Vision Language Models (VLM's). * Fine-tunen van AI-modellen en optimaliseren van prompts voor specifieke use cases.

WI · On-site

$110 - $170/hr

Experiencewith OpenAI or similar LLM frameworks * FamiliaritywithStreamlit,FastAPI, or Flask for building UI/demo tools Requirements Nice to Have Technical Skills: * Priorexperience with building ...

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 ...

LLM apps, agents, RAG, and automated workflows as core components, not bolt-ons. Translate AI policy and risk requirements into working software, partnering with Cyber, Legal, Privacy, and ...

New

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 ...

WI · On-site

$140 - $200/hr

Stay at the frontier of LLM techniques and rapidly incorporate emerging best practices into production systems across SpaceX programs BASIC QUALIFICATIONS: * Bachelor's degree in computer science ...

New

Senior AI/ML Engineer

Milwaukee, WI · On-site

$141K - $193K/yr

Develop advanced LLM-powered product features, including intelligent user copilots, automated diagnostic analysis, smart recommendations, and natural language interfaces. • Inference Architecture:

WI · On-site

$140 - $210/hr

This role focuses on compiler development for our novel LLM accelerator architecture. This is one of several software stacks that seamlessly bridge high-level AI workloads with our custom hybrid ...

Sr. Engineer, AI Platform

Madison, WI · On-site

$99 - $199/hr

Lead the execution of ML, NLP, LLM deliverables in support of the AI strategies. * Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth ...

WI · On-site

You will lead architectural decisions for multi-agent orchestration, RAG pipelines, and LLM infrastructure, partnering with Health100 and CVS Health executives to align technology with business goals.

Sr. Engineer, AI Platform

Madison, WI · On-site

$99K - $198K/yr

Lead the execution of ML, NLP, LLM deliverables in support of the AI strategies. * Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth ...

Lead the execution of ML, NLP, LLM deliverables in support of the AI strategies. * Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth ...

next page

Showing results 1-20

Llm information

What is an LLM?

LLMs, or Large Language Models, are advanced artificial intelligence systems designed to understand and generate human-like text based on vast amounts of data. These models, such as OpenAI's GPT series, are trained on diverse datasets and can perform a range of tasks, including answering questions, writing content, translating languages, and more. LLMs work by predicting the next word in a sequence, allowing them to create coherent and contextually relevant responses. They are widely used in applications like chatbots, virtual assistants, and automated content generation.

What are the key skills and qualifications needed to thrive as an LL.M. graduate?

To thrive as an LLM graduate, you need advanced knowledge of legal principles, strong research and analytical skills, and a prior law degree such as an LLB or JD. Familiarity with legal databases, research tools like Westlaw or LexisNexis, and sometimes bar admission or certification in specific jurisdictions is advantageous. Exceptional written and verbal communication, attention to detail, and cross-cultural competence are standout soft skills in this field. These abilities are crucial for interpreting complex legal issues, advising clients, and succeeding in global or specialized legal practice.

What are some common challenges faced by professionals working with large language models and how can they be addressed?

Professionals working with large language models often encounter challenges such as managing computational resource demands, ensuring data privacy, and mitigating biases in model outputs. Collaboration with data engineers and IT teams is essential to optimize infrastructure and streamline model deployment. Staying updated on best practices and regulatory guidelines helps address ethical concerns and improve model performance. Continuous monitoring and iteration are key to maintaining accuracy and relevance in real-world applications.

What is the difference between Llm vs Paralegal?

AspectLlmParalegal
Required CredentialsLaw degree (JD or equivalent), possibly an LLM for specializationAssociate's degree or certificate in paralegal studies
Work EnvironmentLaw firms, corporate legal departments, academiaLaw firms, corporate legal departments, government agencies
Industry UsageLegal practice, academia, researchLegal support, case preparation, client communication

The main difference is that an Llm is an advanced law degree for specialization or academic purposes, while a paralegal provides legal support and case assistance without being licensed to practice law. Both roles work closely within legal environments, but the Llm is more focused on legal expertise and research, whereas paralegals handle administrative and preparatory tasks.

What jobs can I do with a large language model?

A large language model (LLM) can be used in roles such as AI researcher, NLP engineer, data scientist, or machine learning engineer, focusing on developing and deploying AI applications. These jobs typically require skills in programming, data analysis, and understanding of AI frameworks like TensorFlow or PyTorch.

Which large language model is most in demand?

The most in-demand large language models for jobs like LLM development and deployment are OpenAI's GPT-4 and GPT-3, as well as Google's PaLM and Meta's LLaMA. Skills in fine-tuning, prompt engineering, and understanding these models are highly sought after in the AI industry.

What are the most commonly searched types of Llm jobs in Wisconsin?

The most popular types of Llm jobs in Wisconsin are:

Infographic showing various Llm job openings in Wisconsin as of August 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Senior AI Solutions Engineer

Bruno Independent Living Aids, Inc.

Oconomowoc, WI • On-site

$55.25 - $71.25/hr

Full-time

Re-posted 4 days ago


Job description

Architect, develop, and deploy software solutions at high velocity using an AI-first, agentic development workflow.  This role demands a language-agnostic polyglot developer who leverages LLM-powered coding agents as a force multiplier to deliver 10x the output of traditional development approaches.  Additional responsibilities include system integrations, BI solutions, and supporting Tech-Ops infrastructure on-premises and in-cloud.


AI-FIRST SOFTWARE DEVELOPMENT

  • Scope, design, develop, and deploy software applications, integrations, APIs, and database services using agentic LLM coding workflows as the primary development methodology.
  • Maintain and extend existing ERP customizations and develop new solutions across multiple languages and platforms, selecting the best tool for each task.
  • Maintain and extend integration platform operations (e.g., Jitterbit) and CRM customizations (e.g., Salesforce APEX), leveraging AI-assisted coding for rapid iteration.
  • Participate in review / recommendation of externally purchased IT solutions and services.
  • Manage hardware and software vendor relationships
  • Champion and evangelize AI-first development practices across the IT team; mentor peers on agentic coding workflows, prompt engineering, and LLM-augmented development to accelerate team-wide adoption and output.
  • Design and build custom LLM agent harnesses and multi-agent architectures, including manager/supervisor agent patterns that orchestrate swarms of specialized sub-agents to decompose and execute complex development and business automation tasks.
  • Create and maintain documentation, training materials, and AI workflow playbooks for IT systems, software, integrations, APIs, and development procedures

BUSINESS ANALYSIS

  • Work closely with company managers to identify informational needs and develop solutions to provide efficient information processing and valuable information for business analysis
  • Provide lifecycle support of applications and contribute to the development of new concepts, techniques, and standards
  • Implement and manage long-term, system-wide IT initiatives that align with the company’s business strategy and objectives 

HARDWARE AND PLATFORM SUPPORT

  • Recommend and participate in the deployment, monitoring, maintenance, development, upgrade and support of IT hardware and software including telecommunications, servers, PC’s, operating systems, and office automation equipment – both on premise and in-cloud PaaS & IaaS
  • Benchmark, analyze, report on and make recommendations for improvement of and growth of IT infrastructure and IT systems
  • Recommend efficient and cost-effective technological equipment, systems, platforms and services
  • Identify problematic areas and implement strategic solutions in a timely manner
  • Maintain confidentiality of proprietary information
  • Stay current with rapidly evolving AI/LLM tooling, agentic frameworks, and emerging development paradigms; continuously evaluate and adopt new AI-powered development tools

Education and Experience:

  • Position requires a Bachelor’s degree in computer science or related field and a minimum of 6 years progressive experience with 3 years preferably in a mid-sized manufacturing environment. 

  • Candidate must demonstrate a proven AI-first development workflow using agentic LLM coding tools (e.g., Claude Code, GitHub Copilot Workspace, Cursor, Windsurf, or similar) as their primary development method. 

  • Must be a language polyglot comfortable architecting and delivering solutions across multiple technology stacks rather than being tied to a single language or framework. 

  • Required experience includes SQL, RESTful APIs, system integrations, GIT, BI reports/dashboards, databases, and vendor management. 

  • Proficiency in prompt engineering for code generation, agentic task orchestration, and AI-assisted debugging is essential. 

  • Experience with .NET/C#, JavaScript/TypeScript, Python, or other modern languages expected; experience with Epicor, Jitterbit, and Salesforce preferred. 

  • Strong preference for candidates who have built custom LLM agent harnesses, orchestrated multi-agent swarms under a manager/supervisor agent pattern, or developed agentic pipelines that coordinate specialized sub-agents for complex, multi-step workflows.

Knowledge, Skills and Abilities:

  • Proven expertise with agentic LLM coding tools and AI-assisted development workflows. 
  • Ability to work fluently across multiple programming languages and technology stacks without being dependent on any single ecosystem. 
  • Strong prompt engineering skills for code generation, debugging, and architectural planning. 
  • Familiarity with multi-agent system design, including manager-agent orchestration layers and agent swarm coordination patterns. 
  • Read, analyze, and interpret a variety of information, such as technical procedures, business correspondence, and governmental regulations furnished in written, oral or diagram form. 
  • Effectively present information to employees, management, and customers. 
  • Create business-level written correspondence and verbally present information to large or small groups, both internally and externally. 
  • Requires Microsoft Office proficiency and the ability to operate a variety of standard office equipment. 

Working Conditions/Physical Demands:

  • Office environment, with occasional lifting and bending