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Temporary Large Language Model Llm Jobs (NOW HIRING)

AI Software Engineer I

Logan, UT · On-site

$68K - $117K/yr

Apply modern AI development frameworks, large language model (LLM) APIs, and integration patterns under guidance. * Identify and escalate bugs, performance issues, and integration failures to senior ...

Apply modern AI development frameworks, large language model (LLM) APIs, and integration patterns under guidance. * Identify and escalate bugs, performance issues, and integration failures to senior ...

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Temporary Large Language Model Llm information

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How much do temporary large language model llm jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for temporary large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.

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 are Temporary Large Language Model (LLM) roles?

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 Large Language Model (LLM) Engineer, and why are they important?

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.
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Infographic showing various Temporary Large Language Model Llm job openings in the United States as of July 2026, with employment types broken down into 47% Full Time, 15% Part Time, and 38% Contract. Highlights an 61% In-person, 8% Hybrid, and 31% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.
Principal AI Software Engineer (TS/SCI + Poly)

Principal AI Software Engineer (TS/SCI + Poly)

Aperio Global

Fort George G Meade, MD • On-site

$149K - $200K/yr

Other

Posted 18 days ago


Job description

We are seeking a Principal AI Software Engineer to support the exciting Corporate Directory Services mission. You will work closely with mission stakeholders to lead the development of advanced Artificial Intelligence and Machine Learning (AI/ML) solutions, intelligence mission workflows, and emerging analytic capabilities. This role is responsible for designing, developing, prototyping, and operationalizing AI-enabled applications that automate complex intelligence processes, discover emergent intelligence value, and accelerate mission outcomes. You will also  work across multiple technical domains including software engineering, data science, machine learning, and large language model (LLM) integration to deliver innovative capabilities from proof-of-concept through operational deployment.

Mission Focus:

Collaborate closely with customers to drive the rapid development, evaluation, and transition of AI/ML-enabled mission capabilities that enhance operational analysis and intelligence workflows. Leverage emerging technologies, scalable software architectures, and advanced analytics to automate discovery, accelerate insight generation, and deliver production-ready solutions across diverse mission domains. Shape technical strategy and best practices to ensure effective deployment, sustainment, and evolution of AI-enabled mission systems

Technical Proficiency:

Proficient in current AI/ML technologies such as classification, clustering, collaborative filtering, search, and retrieval using techniques such as but not limited to  deep neutral networks (DNN), recurrent neural networks (RNN), attention-based transformers, etc. Experience in current large language models (LLM) for representative and generative tasks.

Qualifications:

Bachelor's degree plus 11-years of relevant experience or equivalent. Proficiency with object-oriented languages (JAVA, Python) and experience with Jupyter Notebooks

Security Clearance: Active TS/SCI with Polygraph required (CCA) 


Nice To Have:

Proficiency in approaches to retrieval augmented generation (RAG), model context protocol (MCP) and other recent technologies supporting agentic AI. Foundational knowledge of statistics related to parametric probability distributions, nonparametric probability distributions, Bayesian analysis, and covariance matrices. Proficiency in agentic systems that can automatically carry out mission goals with limited supervision.

Salary Range: 207,000-227,000