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Temporary Large Language Model Llm Jobs in Utah (NOW HIRING)

WorkBay

Data & Infrastructure Engineer

Draper, UT · On-site

$107K - $128K/yr

Exposure to AI/LLM architecture -- understanding how large language models consume data and how to structure pipelines that support AI-driven applications * Experience with container-based deployment ...

WorkBay

Data & Infrastructure Engineer

Draper, UT · On-site

$107K - $128K/yr

Exposure to AI/LLM architecture understanding how large language models consume data and how to structure pipelines that support AI-driven applications * Experience with container-based deployment ...

Deloitte

Google AI Lead Architect

Salt Lake City, UT

$53.50 - $73.25/hr

LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and ...

Utah State University

Language Coach (ASL)

Logan, UT

$40 - $50/hr

As a Deaf language model and cultural expert, the coach facilitates authentic language experiences ... Over the past 50 years the IDRPP has grown into one of the largest UCEDD programs in the nation and ...

Utah State University

Language Coach (ASL)

Logan, UT · On-site

$40 - $50/hr

As a Deaf language model and cultural expert, the coach facilitates authentic language experiences ... Over the past 50 years the IDRPP has grown into one of the largest UCEDD programs in the nation and ...

System One

AI Engineer

Salt Lake City, UT · On-site

Hands-on experience with: o AI/ML and Generative AI o Large Language Models (LLMs) and prompt engineering o RAG architectures and vector databases o MLOps practices * Experience with Docker ...

System One

AI Engineer

Salt Lake City, UT · On-site

Hands-on experience with: o AI/ML and Generative AI o Large Language Models (LLMs) and prompt engineering o RAG architectures and vector databases o MLOps practices * Experience with Docker ...

System One

AI Engineer

Salt Lake City, UT · On-site

Hands-on experience with: o AI/ML and Generative AI o Large Language Models (LLMs) and prompt engineering o RAG architectures and vector databases o MLOps practices * Experience with Docker ...

Adobe

Senior Product Manager, Chief Accounting Office

Lehi, UT · On-site

$118K - $156K/yr

... large language models (LLMs) within a world-class finance ecosystem. What You'll Do * S/4HANA ... LLM-powered interfaces, predictive cash flow forecasting and working capital optimization, real ...

Stackruit Ltd.

Senior AI/ML Engineer

Draper, UT · On-site

$100 - $130/hr

Experience with large language models (LLMs) and prompt engineering. * A passion for innovation and creative problem-solving. Why BambooHR? * Make a real impact on the future of work with AI. * Enjoy ...

New

CardWorks

Director, Data Science

South Jordan, UT

Utilize Large Language Models (LLMs) to analyze and summarize earnings calls, SEC filings, analyst reports, press releases, industry publications, and competitor disclosures. * Develop Retrieval ...

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Temporary Large Language Model Llm information

What is the difference between Temporary Large Language Model Llm vs Data Scientist?

AspectTemporary Large Language Model LlmData Scientist
Required CredentialsTypically no formal degree, but expertise in AI/ML and programmingUsually requires a degree in Computer Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesData analysis, modeling, and business insights in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, and more
Common Search & ComparisonFocuses on AI model deployment and developmentFocuses on data analysis and insights

The main difference is that a Temporary Large Language Model Llm is an AI system or model used for language processing, while a Data Scientist analyzes data to generate insights. The Llm is a tool or product, whereas the Data Scientist is a professional role that may utilize models like Llm in their work.

What are the typical challenges faced by professionals working in a temporary large language model LLM role, and how can they be addressed?

Professionals in temporary Large Language Model (LLM) roles often encounter challenges such as quickly adapting to new datasets, ensuring data privacy, and optimizing model performance within tight deadlines. Since these roles are project-based, there may be limited onboarding time, requiring a strong ability to learn and collaborate rapidly with cross-functional teams like data engineers and product managers. To succeed, it's helpful to be proactive in seeking clarification, documenting work thoroughly, and staying updated on the latest advancements in LLM technologies.

What is a temporary large language model LLM?

Temporary Large Language Model (LLM) roles involve short-term positions where individuals work with or support the development, training, or deployment of large language models like GPT or similar AI technologies. These roles may include tasks such as data annotation, prompt engineering, model evaluation, or assisting in content moderation powered by LLMs. Temporary LLM roles are often project-based and can be found in tech companies, research labs, or organizations utilizing AI for various applications. They generally require familiarity with AI concepts, attention to detail, and sometimes programming skills.

What are the key skills and qualifications needed to thrive as a temporary large language model LLM?

To thrive as a Large Language Model (LLM) Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Proficiency with tools like Python, TensorFlow or PyTorch, and experience with cloud platforms and version control systems is typically required. Strong problem-solving skills, attention to detail, and effective communication help engineers collaborate and innovate in complex projects. These skills are crucial for developing, fine-tuning, and deploying LLMs that deliver accurate and ethical AI solutions.
What are the most commonly searched types of Large Language Model Llm jobs in Utah? The most popular types of Large Language Model Llm jobs in Utah are:
What are popular job titles related to Temporary Large Language Model Llm jobs in Utah? For Temporary Large Language Model Llm jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Temporary Large Language Model Llm jobs in Utah look for? The top searched job categories for Temporary Large Language Model Llm jobs in Utah are:
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Temporary Large Language Model Llm jobs near you

Data & Infrastructure Engineer

WorkBay

Draper, UT • On-site

$107K - $128K/yr

Full-time

PTO

Re-posted 28 days ago

Job description

Company: WorkBay
Location: Salt Lake City, UT area | On-Site
Employment Type: Full-Time
Compensation: Based on experience


About WorkBay
WorkBay is the largest owner/operator of micro-bay industrial warehouse parks in the United 
States. Fully vertically integrated, we develop, acquire, and manage micro-bay properties across 
the country's top markets. We move fast, think strategically, and build systems that scale — and 
we're looking for an engineer who does the same.


Position Overview
We are seeking a skilled and motivated Data & Infrastructure Engineer to own and evolve the 
data platform that powers WorkBay's operations, analytics, and strategic decision-making. You 
will maintain and extend our data pipelines, API integrations, cloud deployments, and AI powered tools — ensuring the integrity, security, and reliability of our proprietary systems as we continue to scale.


Key Responsibilities

  • Maintain and extend scheduled data sync pipelines that pull from third-party APIs into our 
    PostgreSQL database
  • Monitor and troubleshoot cloud deployments across Vercel (serverless functions) and 
    Railway (container services), including uptime, logs, and performance
  • Build and manage API integrations — designing endpoints, handling authentication, and 
    ensuring reliability across internal and external services
  • Enforce data integrity standards including validation, cleansing, deduplication, and quality 
    assurance across complex multi-source data
  • Implement and maintain data security protocols to protect WorkBay's proprietary 
    information, including access controls and encryption
  • Support and extend our AI infrastructure, prompt configurations, evaluation suites, and cost 
    monitoring
  • Own database schema migrations, indexing, and query optimization in PostgreSQL
  • Manage version-controlled codebases using GitHub, including code reviews, CI/CD pipelines, 
    and deployment workflows
  • Collaborate with leadership to design data-driven tools and dashboards that support 
    operational decision-making
  • Document data architecture, runbooks, and processes to ensure organizational continuity


Qualifications

Required

  • 3–5 years of professional experience in data engineering, platform engineering, or a related 
    field
  • Strong proficiency in Python and SQL
  • Production experience with PostgreSQL (schema design, migrations, query optimization)
  • Experience building and consuming REST APIs
  • Proficiency with GitHub and modern version control workflows (branching, PRs, CI/CD)
  • Experience with serverless platforms (Vercel, AWS Lambda, Cloudflare Workers, or similar)
  • Comfort with Linux CLI, shell scripting, and remote server management
  • Strong problem-solving skills with the ability to work independently and manage multiple 
    priorities


Preferred

  • Exposure to AI/LLM architecture — understanding how large language models consume 
    data and how to structure pipelines that support AI-driven applications
  • Experience with container-based deployment platforms (e.g., Railway, Docker, Fly.io)
  • Experience with CRM integrations (e.g., Salesforce, HubSpot) or property management systems 
    (e.g., Yardi, MRI, RealPage)
  • Background in real estate, property management, or commercial real estate tech
  • Experience with ETL/ELT patterns and workflow orchestration (e.g., APScheduler, Airflow, 
    Dagster)
  • Familiarity with React/TypeScript (not required, but helpful for full-stack debugging)
  • Experience in a high-growth or scaling company environment


What We Offer

  • Competitive compensation based on experience
  • Generous PTO policy
  • Opportunity to own critical infrastructure at a fast-scaling company in commercial real estate
  • A lean, entrepreneurial environment where your work directly impacts company growth
  • Cutting-edge AI/ML workflows for real estate — you'll work with LLM APIs, prompt engineering, and AI-powered automation in a live business context


WorkBay is an equal opportunity employer. We celebrate diversity and are committed to 
creating an inclusive environment for all employees