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Part Time Large Language Model Llm Jobs (NOW HIRING)

Booz Allen Hamilton, Inc.

AI/ML Engineer, Lead

Ashburn, VA · On-site +1

$104K - $138K/yr

Design, build, and deploy large language model (LLM) and agentic AI solutions, including multi ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Implicit

AI Engineer (US-Based / Part-Time)

Strong experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG ... Experience evaluating and benchmarking LLM performance. What We Offer * Competitive compensation.

Implicit

AI Engineer (US-Based / Part-Time)

Strong experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG ... Experience evaluating and benchmarking LLM performance. What We Offer * Competitive compensation.

Pika

Research Intern (BS/MS/PhD)

Palo Alto, CA · On-site

Familiarity with multimodal large language models (MLLMs) is valued as a bonus. This internship is ... Flexible part-time and full-time internship terms are available. What You'll Do * Work directly on ...

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

As of Sep 14, 2026, the average hourly pay for part time 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 a part time large language model LLM?

A Part Time Large Language Model (LLM) role typically involves working with large language models, such as GPT or similar AI systems, on a part-time basis. Responsibilities may include training, fine-tuning, evaluating, or deploying LLMs to solve specific problems or improve existing language technologies. These roles often require knowledge of natural language processing, machine learning, and programming. Part-time positions allow for flexible working hours and may be suitable for students, researchers, or professionals looking to contribute to AI projects without a full-time commitment.

What skills and qualifications are needed to thrive as a part time large language model LLM?

To thrive as a Part-Time 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 or equivalent experience. Proficiency with tools and frameworks like Python, TensorFlow, PyTorch, and experience working with LLM architectures such as GPT or BERT is typically required. Strong analytical thinking, communication skills, and the ability to collaborate effectively in a remote or distributed environment are valuable soft skills. These competencies are crucial for successfully developing, fine-tuning, and deploying advanced language models that meet organizational goals.

What are common challenges faced when working part time with large language models LLMs?

Part-time professionals working with Large Language Models often face challenges in keeping up with rapid advancements in AI technologies and adapting to evolving best practices. Balancing limited work hours with the need to stay updated on new research, tools, and model updates can be demanding. Additionally, coordinating with full-time team members and integrating contributions within tight timelines requires effective communication and collaboration skills. However, the flexible schedule can also provide opportunities for continuous learning and professional growth.

What is the difference between Part Time Large Language Model Llm vs Part Time Data Annotator?

AspectPart Time Large Language Model LlmPart Time Data Annotator
Required CredentialsKnowledge of NLP, AI, and machine learning conceptsAttention to detail, basic understanding of data labeling
Work EnvironmentRemote or office-based, involving AI development teamsRemote or on-site, working with datasets and labeling tools
Employer & Industry UsageTech companies, AI research labs, startupsData companies, AI firms, machine learning projects

While both roles support AI development, a Part Time Large Language Model Llm focuses on understanding and improving language models, requiring technical knowledge. A Part Time Data Annotator primarily labels data to train models, emphasizing accuracy and attention to detail. The roles differ in technical complexity but are both essential in AI workflows.

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Part Time Large Language Model Llm jobs near you
Infographic showing various Part Time Large Language Model Llm job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

Senior AI Test Engineer (Remote)

Sterling, VA • Remote

TestPros
IT Services • 11 - 50 employees
Learn more about TestProsexternal

Part-time

Re-posted 4 days ago

Job description

TestPros delivers innovative independent IT assessment solutions to critical challenges facing the nation and the world.  We support the U.S. Federal/State/Local Government and Commercial clients within the continental USA. TestPros is dedicated to making lives better, safer and more secure.
TestPros is seeking a Senior Artificial Intelligence (AI) System Test Engineer with an analytical, customer-focused mindset and experience with the OWASP AI Testing Guide and other guidelines from NIST, ISO, and IEEE.
Start: Future projects in late 2026 or 2027 (not an immediate job opening) 
Type: Part-time consulting
Overview
Focus: Software test end evaluation
Regulatory Basis: OWASP AI Testing Guide, NIST AI Risk Management Framework (AI RMF), NIST Cybersecurity Framework (CSF) Cyber AI Profile, AI Bills of Materials (AI-BOMs), NSA AI Security Guidelines.
Location: Remote, with occasional travel to customer sites or TestPros labs in Sterling, VA
This role evaluates AI systems and software for alignment with the intended functions and features, plus additional assessment focused on AI-specific validation, including model robustness, data integrity, adversarial defense, performance, usability, reliability, security, maintainability, safety, and other aspects of overall quality.
.
Key Responsibilities:
Develop and execute test plans and evaluate software for compliance with the OWASP AI Testing Guide and other guidance, create defect and remediation records, capture test evidence and document defects with clear reproduction steps and severity ratings, report results to senior management and stakeholders.
Required Skills.

  • Bachelor's degree in computer science, engineering or a related field.
  • 10+ years of experience in Software/System Testing and Quality Engineering (QE), including enterprise-scale transformation programs.
  • Solid understanding of and experience with the OWASP AI Testing Guide, and the NIST AI Risk Management Framework (RMF).
  • 4+ years hands-on experience defining the testing strategy for large scale programs and ensuring requirements traceability throughout the system development lifecycle. Experience should include leading the testing efforts, including experience with all phases of testing: system integration, user acceptance, and performance testing.
  • A deep understanding of testing planning and associated delivery challenges.
  • A strong understanding of the various approaches used in testing techniques - white-box, black-box, load testing, coverage testing and regression testing.
  • Proven experience in defining and executing QE transformation strategy.
  • Hands-on expertise in Agentic AI / GenAI frameworks (e.g., LangChain, AutoGen, CrewAI, Cursor, etc.).
  • Experience working in Cloud, Web and Mobile Testing platforms - Saucelabs, Browerstack are preferred.
  • Hands-on experience with machine learning models.
  • Experience in Python NLTK or similar natural language processing technology.
  • Practical experience implementing AI-driven QE solutions such as:
  • Autonomous test generation
  • Self-healing automation
  • Defect prediction and intelligent triaging
  • Expertise in test automation tools (Selenium, Playwright, Cypress, etc.).
  • Strong experience with CI/CD pipelines and DevOps integration (GitHub).
  • Solid understanding of API, microservices, and cloud-native architectures.
  • Experience evaluating or testing Artificial Intelligence (AI) Large Language Model (LLM)-based application features (e.g., chatbots, copilots, RAG-based systems), including prompt-response validation and hallucination/edge-case testing.
  • Exposure to AI-assisted defect triage or root-cause analysis tools that reduce manual investigation time.
  • Experience with cloud platforms (AWS, Azure, GCP) in QE/AI context.
  • Exposure to self-healing test automation frameworks (AI-driven locator repair, visual AI testing).
  • Understanding of responsible AI/testing governance principles (bias detection, explainability, model validation) as applied to QE.
  • Experience contributing to or influencing AI-adoption roadmaps within a testing/QE organization.
  • Experience implementing testing best practices specific to the test planning and execution processes and gaining buy-in for changes from executives.
Preferred Skills
  • Experience with test automation tools, and AI assisted test tools
  • Familiarity with JIRA project/test management system
  • Knowledge of other IT compliance such as WCAG/Accessibility, IT Security, IT Privacy
  • Professional certifications in the software testing discipline

Work Environment: Hands-on testing role. Remote-friendly with occasional on-site or hybrid work as needed.
Rate: $50-80/hr. 1099 or Corp. To Corp.). This range represents a good-faith estimate and is not a guarantee; final compensation is determined by factors such as experience, qualifications, and government contract labor rate requirements and may fall outside the stated range. 
Equal Opportunity Employer
TestPros is an equal-opportunity employer and does not discriminate in employment based on race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or any other non-merit factor.
Offer Considerations
TestPros considers several factors when extending an offer, including but not limited to, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, geographic location, education, and certifications.
Federal Compliance
As a federal contractor, TestPros is subject to all federal and state mandates and/or other customer requirements.

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