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Temporary Large Language Model Llm Jobs (NOW HIRING)

Straive

LLM Engineer

San Francisco, CA · On-site +1

The ideal candidate will have a deep understanding of large language models (LLMs) and their application in real-world scenarios. As an LLM Engineer at Straive, you will play a crucial role in ...

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

As of May 29, 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 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.

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 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.

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Temporary Large Language Model Llm jobs near you
Infographic showing various Temporary Large Language Model Llm job openings in the United States as of May 2026, with employment types broken down into 3% As Needed, 24% Full Time, 68% Part Time, and 5% Contract. Highlights an 93% Physical, and 7% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

Data Scientist (Python | LLM | AWS)

Purple Drive Technologies

Los Angeles, CA • On-site

Full-time

Posted 25 days ago

Job description

Overview:
Role Summary:
We are seeking an experienced Data Scientist with hands-on expertise in analytics, machine learning, and cloud technologies. The ideal candidate will design and implement data-driven solutions using Python, AWS, and modern DevOps tools, while collaborating with business teams to deliver actionable insights-preferably within the healthcare domain.
Key Responsibilities:
  • Develop and deploy predictive models for classification, regression, NLP, and deep learning use cases.
  • Work on large language model (LLM) applications and data pipelines.
  • Analyze structured and unstructured data to derive insights and recommendations.
  • Collaborate cross-functionally to translate business needs into data science solutions.
  • Implement workflows using CI/CD, Docker, and Terraform for scalable deployment.
  • Maintain GitHub repositories and contribute to reusable data science assets.
  • Build and visualize data stories to communicate findings to stakeholders.

Required Skills & Experience:
  • Strong proficiency in Python (end-to-end data workflows).
  • Experience with LLMs, NLP, and deep learning frameworks.
  • Familiarity with AWS services such as Bedrock, DynamoDB, S3, and Fargate.
  • Experience with Docker, Terraform, and Infrastructure as Code.
  • Exposure to Node.js, React, and modern web technologies.
  • Solid database and SQL knowledge.
  • Strong communication and storytelling skills.
  • Prior experience in healthcare or healthcare sales preferred.

Apply