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Assistant Llm Training Jobs in Arizona (NOW HIRING)

Associate AI Solution Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

Architect and Design: assist in the design and development of enterprise-grade application ... training, defining support procedures. * Assisting clients with application architecture design ...

We offer comprehensive training for all new employees. The ideal candidate for this role must have ... Following standard procedures to conduct system changes * Assist continuous improvement initiatives ...

We offer comprehensive training for all new employees. The ideal candidate for this role must have ... Following standard procedures to conduct system changes * Assist continuous improvement initiatives ...

Assistant Llm Training information

What is an assistant LLM training?

Assistant LLM Training jobs typically involve supporting the development, fine-tuning, and evaluation of large language models (LLMs) like GPT or similar AI systems. Individuals in these roles may help gather and curate training data, annotate or review outputs, and assist in testing model performance. They often work closely with machine learning engineers and data scientists to ensure the LLMs produce accurate, ethical, and high-quality responses. These positions may also include monitoring for biases, suggesting improvements, and maintaining documentation related to model training.

What are the key skills and qualifications needed to thrive as an assistant LLM training?

To thrive as an Assistant LLM Training Specialist, you need a solid understanding of machine learning concepts, data preprocessing, and natural language processing, often supported by a degree in computer science or a related field. Familiarity with Python, deep learning frameworks such as TensorFlow or PyTorch, and experience with data annotation tools are typically required. Strong attention to detail, problem-solving skills, and the ability to collaborate effectively with data scientists and engineers set standout candidates apart. These competencies ensure the accurate preparation and management of data crucial for developing effective large language models.

What are some typical challenges faced by assistant LLM training professionals, and how can they be addressed?

Assistant LLM Training professionals often encounter challenges such as ensuring high-quality data annotation, managing large and complex datasets, and keeping up with evolving model requirements. Effective communication with data scientists and engineers is crucial to align on project goals and annotation standards. Staying organized and proactive in seeking feedback can help address ambiguities in training data, while continuous learning about new tools and best practices in machine learning annotation can further enhance overall performance.

What is the difference between Assistant Llm Training vs Data Annotator?

AspectAssistant Llm TrainingData Annotator
Required CredentialsTypically a degree in AI, computer science, or related fieldHigh school diploma or equivalent; training often provided
Work EnvironmentOffice or remote, collaborative with AI teamsMostly remote or on-site, focused on data labeling
Industry UsageAI development, machine learning projectsData preparation for AI and ML models
Common Search & ComparisonOften compared for roles supporting AI trainingCompared for data labeling and annotation tasks

Assistant Llm Training involves preparing and fine-tuning language models, requiring technical skills and relevant degrees. Data Annotator focuses on labeling data to train AI models, often with minimal formal credentials. Both roles support AI development but differ in technical complexity and responsibilities.

What are the most commonly searched types of Llm Training jobs in Arizona?

The most popular types of Llm Training jobs in Arizona are:

What are popular job titles related to Assistant Llm Training jobs in Arizona?

For Assistant Llm Training jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Assistant Llm Training jobs in Arizona look for?

The top searched job categories for Assistant Llm Training jobs in Arizona are:

What cities in Arizona are hiring for Assistant Llm Training jobs?

Cities in Arizona with the most Assistant Llm Training job openings:

Campus Graduate Masters Full-Time Engineer - 2027 AI Engineer I, Enterprise Technology Services- Pho

American Express

Phoenix, AZ • On-site

$78K - $124K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 5 days ago


American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

25th of 154 rated financial services


Job description


Business Unit / Role Specific Info
The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company's technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
At American Express, we empower technologists to learn, innovate, and make an impact from day one. As an AI Engineer I in Enterprise Technology Services, you'll join a full-time graduate program and contribute to technology work that helps teams explore, build, test, and responsibly scale AI-enabled solutions.
In this role, you may support work across machine learning, generative AI, intelligent automation, data pipelines, retrieval patterns, model evaluation, LLM integrations, AI agents, agentic workflows, and AI-enabled software features. You'll collaborate with engineering, product, data, security, risk, and business partners to help deliver enterprise AI solutions responsibly, reliably, and securely.
Responsibilities
Responsibilities & What Type of Work to Expect
  • Support the development, testing, and integration of AI / ML models, LLM integrations, intelligent services, or data retrieval pipelines under guidance.
  • Assist with data collection, preprocessing, transformation, and validation to support model training, testing, evaluation, and implementation.
  • Contribute to debugging and improving AI enabled solutions to strengthen performance, reliability, explainability, maintainability, and quality.
  • Support AI capabilities such as model training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents, or agentic workflows.
  • Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions aligned to business requirements.
  • Document model parameters, prompts, assumptions, data pipelines, integrations, and technical decisions to support reproducibility and knowledge sharing.
  • Participate in Agile development practices, including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies.
  • Assist in ensuring AI systems and AI-enabled features align with enterprise expectations for reliability, safety, governance, security, compliance, and appropriate escalation.

Qualifications
Minimum Qualifications
  • Must have earned a Master's degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Computer Engineering, Software Engineering, or another technical field before the full-time start date.
  • Knowledge of Python and foundational data processing technologies.
  • Foundational understanding of computer science concepts, including data structures, algorithms, object-oriented programming, debugging, testing, and problem solving.
  • Foundational understanding of machine learning concepts such as supervised learning, unsupervised learning, model training, evaluation, feature engineering, and experimentation.
  • Introductory understanding of modern AI systems, including LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools, or generative AI applications.
  • Ability to support AI/ML development, testing, documentation, integration, or data pipeline activities under guidance.
  • Awareness of responsible AI expectations, including reliability, safety, governance, security, privacy, compliance, and appropriate escalation when work is unclear or outside standard guidance.
  • Strong communication, collaboration, documentation, and learning agility with the ability to work effectively across technical and non-technical teams.

Preferred Qualifications
  • Master's degree candidates with an expected graduation date between December 2026 and June 2027.
  • Experience through academic coursework, research, projects, open-source contributions, internships, hackathons, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies.
  • Interest in machine learning, generative AI, natural language processing, intelligent automation, data engineering, agentic AI, or AI-enabled software development.
  • Familiarity with NLP techniques and model concepts such as fuzzy matching, embeddings, BERT, transformers, LLMs, or other modern language models.
  • Exposure to LLM APIs or similar AI models, including prompt engineering, prompt evaluation, tools, function calling, retrieval patterns, or agent workflow concepts.
  • Experience or coursework involving machine learning algorithms and applying them to practical or real-world problems.
  • Familiarity with APIs, data pipelines, ETL processes, cloud environments, containerized development, model deployment patterns, or monitoring.
  • Awareness of CI/CD, version control, testing, code reviews, Agile development, and collaborative software engineering workflows.
  • Exposure to version control systems such as Git and collaborative software development workflows.
  • Curiosity for AI powered developer tools, responsible AI practices, governance, security, model documentation, and enterprise-scale delivery.

Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Bonus incentives
  • 6% Company Match on retirement savings plan
  • Free financial coaching and financial well-being support
  • Comprehensive medical, dental, vision, life insurance, and disability benefits
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
US Job Seekers - Click to view the "Know Your Rights" poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster.
The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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