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Temporary Large Language Model Llm Jobs in Alabama

IGNITE

JUNIOR SOFTWARE DEVELOPER

Huntsville, AL · On-site

$62K - $81K/yr

The developer will work with senior engineers to integrate large language models with internal applications, data sources, simulations, and automated workflows. Job Requirements Primary ...

Vultus Inc

Senior Data Scientist

Birmingham, AL · On-site +1

$130K - $170K/yr

Generative AI * Large Language Models (LLMs) * RAG (Retrieval-Augmented Generation) * MLOps ... Experience with Generative AI and LLM-based applications. * Knowledge of MLOps and model deployment ...

Mesa Associates Inc.

AI Program Lead

Madison, AL

LLM Operations (LLMOps): Ability to operationalize large language models efficiently, including monitoring, reliability, and cost control. * Data governance & security: Working knowledge of PII, data ...

Mesa Associates, Inc.

AI Program Lead

Madison, AL

LLM Operations (LLMOps): Ability to operationalize large language models efficiently, including monitoring, reliability, and cost control. * Data governance & security: Working knowledge of PII, data ...

Mesa Associates, Inc

AI Program Lead

Madison, AL · On-site

Proficiency in Python and familiarity with frameworks such as PyTorch or TensorFlow. • LLM Operations (LLMOps): Ability to operationalize large language models efficiently, including monitoring ...

Mesa Accosiates

AI Program Lead

Madison, AL · On-site

LLM Operations (LLMOps): Ability to operationalize large language models efficiently, including monitoring, reliability, and cost control. * Data governance & security: Working knowledge of PII, data ...

Banner Defense, Inc.

AI Engineer

Huntsville, AL · On-site

$130K - $141K/yr

... large language models, agentic workflows, orchestration frameworks, and supporting software ... Familiarity with modern AI application patterns, including LLM-based applications, RAG, prompt ...

Banner Defense, Inc.

AI Engineer

Huntsville, AL

... large language models, agentic workflows, orchestration frameworks, and supporting software ... Familiarity with modern AI application patterns, including LLM-based applications, RAG, prompt ...

Banner Defense, Inc.

AI Engineer

Huntsville, AL · On-site

$130K - $141K/yr

... large language models, agentic workflows, orchestration frameworks, and supporting software ... Familiarity with modern AI application patterns, including LLM-based applications, RAG, prompt ...

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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 Alabama? The most popular types of Large Language Model Llm jobs in Alabama are:
What are popular job titles related to Temporary Large Language Model Llm jobs in Alabama? For Temporary Large Language Model Llm jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Temporary Large Language Model Llm jobs in Alabama look for? The top searched job categories for Temporary Large Language Model Llm jobs in Alabama are:
Temporary Large Language Model Llm jobs near you
Infographic showing various Temporary Large Language Model Llm job openings in Alabama as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

JUNIOR SOFTWARE DEVELOPER

Ignite Fueling Innovation

Huntsville, AL

$62K - $81K/yr

Full-time

Posted 21 days ago

Job description

Igniters operate in the world's most demanding environment. Igniters are self-motivated, mission-driven, and relentless in solving the Warfighters' hardest problems. We move fast, think differently, and execute with precision to tackle high-stakes challenges across AI/ML, space and missile defense intelligence, EMSO, advanced analytics, and programmatic domains.

As an employee-owned SDVOSB headquartered in Huntsville, AL, our team delivers mission-critical impact for the Army, Air Force, Space Force, MDA, NASA, DIA, and FBI. Ignite exists to outpace the threat and deliver results that matter in the moments that count. We are seeking a Junior Software Developer to support the development of AI-enabled applications, agentic workflows, Model Context Protocol (MCP) services, and reusable software tools.

The developer will work with senior engineers to integrate large language models with internal applications, data sources, simulations, and automated workflows.Primary Responsibilities Develop and maintain Python-based applications, services, and automation tools. Build and integrate MCP servers, tools, resources, and client applications. Support agentic workflows that use large language models to select tools, perform multi-step tasks, and process results

Integrate applications with OpenAI-compatible APIs and locally hosted language models. Create configuration-driven tools and workflows with minimal hard-coded behavior. Develop REST APIs and backend services for AI-enabled applications.

Write unit tests, troubleshoot software issues, and maintain technical documentation. Use Git-based development processes, code reviews, and continuous integration. Assist with containerizing and deploying applications in offline or restricted environments.

Required Qualifications Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Mathematics, Physics, or a related technical field. Experience developing software in Python through coursework, internships, personal projects, or professional work. Familiarity with object-oriented programming, APIs, JSON, and asynchronous programming.

Basic understanding of large language models, prompt engineering, tool calling, or agentic application patterns. Experience using Git or another version-control system. Ability to communicate technical information and work effectively as part of a development team.

U.S. citizenship and the ability to obtain and maintain a U.S. Government TS/SCI security clearance

Desired Experience Experience with some of the following is preferred but not required: Model Context Protocol, FastMCP, or the official MCP Python SDK OpenAI SDK or other OpenAI-compatible APIs LangGraph, LangChain, Agno, Semantic Kernel, or similar agent frameworks FastAPI, Pydantic, HTTPX, asyncio, and Uvicorn Pytest and automated software testing Docker and containerized development Retrieval-augmented generation, embeddings, or vector databases Local or offline large language model deployment Linux development environments and basic command-line tools Ideal Candidate The ideal candidate is curious, motivated, and comfortable learning unfamiliar technologies. They should enjoy building practical software, experimenting with emerging AI capabilities, and turning prototypes into reliable, maintainable tools. Direct professional experience with every technology listed above is not expected.Primary Responsibilities Develop and maintain Python-based applications, services, and automation tools

Build and integrate MCP servers, tools, resources, and client applications. Support agentic workflows that use large language models to select tools, perform multi-step tasks, and process results. Integrate applications with OpenAI-compatible APIs and locally hosted language models.

Create configuration-driven tools and workflows with minimal hard-coded behavior. Develop REST APIs and backend services for AI-enabled applications. Write unit tests, troubleshoot software issues, and maintain technical documentation.

Use Git-based development processes, code reviews, and continuous integration. Assist with containerizing and deploying applications in offline or restricted environments. Required Qualifications Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Mathematics, Physics, or a related technical field.

Experience developing software in Python through coursework, internships, personal projects, or professional work. Familiarity with object-oriented programming, APIs, JSON, and asynchronous programming. Basic understanding of large language models, prompt engineering, tool calling, or agentic application patterns.

Experience using Git or another version-control system. Ability to communicate technical information and work effectively as part of a development team. U.S

citizenship and the ability to obtain and maintain a U.S. Government TS/SCI security clearance. Desired Experience Experience with some of the following is preferred but not required: Model Context Protocol, FastMCP, or the official MCP Python SDK OpenAI SDK or other OpenAI-compatible APIs LangGraph, LangChain, Agno, Semantic Kernel, or similar agent frameworks FastAPI, Pydantic, HTTPX, asyncio, and Uvicorn Pytest and automated software testing Docker and containerized development Retrieval-augmented generation, embeddings, or vector databases Local or offline large language model deployment Linux development environments and basic command-line tools Ideal Candidate The ideal candidate is curious, motivated, and comfortable learning unfamiliar technologies

They should enjoy building practical software, experimenting with emerging AI capabilities, and turning prototypes into reliable, maintainable tools. Direct professional experience with every technology listed above is not expected.

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