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Generative Ai Engineer Internship Jobs in Nevada

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Generative AI (diffusion models, fine-tuning, RAG) * AI Engineering & MLOps * AI Engineering & MLOps * Model training, deployment, monitoring, and retraining * Feature stores, vector databases, and ...

Virtusa Corporation

Systems Architect

Las Vegas, NV · On-site

$232K/yr

... LLM as Judge Generative AI Java Full Stack Development Java FSD API Development REST APIs ... Programming OpenAI ChatGPT Anthropic Claude Microsoft AI Meta Llama Large Language Models LLM ...

Deloitte

Senior Forward Deployed Engineer- AWS

Las Vegas, NV · On-site

$99K - $137K/yr

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

Deloitte

Lead Forward Deployed Engineer - AWS

Las Vegas, NV

$97K - $128K/yr

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

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Generative Ai Engineer Internship information

What is a generative AI engineer internship?

A Generative AI Engineer Internship is a temporary position where interns work on developing and optimizing AI models that generate content, such as text, images, or code. Interns typically assist in training, fine-tuning, and testing deep learning models, often using frameworks like TensorFlow or PyTorch. They may also work with large datasets, implement prompt engineering, and collaborate with researchers or engineers. This role provides hands-on experience in machine learning, model deployment, and AI ethics, helping interns build expertise in the field.

What kinds of projects or tasks do generative AI engineer interns typically work on during their internship?

Generative AI Engineer Interns usually contribute to projects involving model architecture development, data preprocessing, and evaluation of generative algorithms for tasks like text, image, or audio synthesis. Interns often collaborate closely with senior engineers and data scientists, participate in code reviews, and assist in optimizing model performance or preparing proofs of concept for new generative applications. You may also be involved in researching state-of-the-art methods and presenting your findings to the team. These experiences offer valuable hands-on exposure and are designed to prepare you for a future full-time role in AI engineering.

What are the key skills and qualifications needed to thrive in the generative AI engineer internship position, and why are they important?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, deep learning frameworks, and experience with programming languages such as Python. Familiarity with tools like TensorFlow, PyTorch, and version control systems is often expected, and relevant coursework or certifications in AI or data science are advantageous. Strong problem-solving abilities, communication skills, and eagerness to learn help distinguish top candidates in collaborative, fast-paced environments. These skills are vital for effectively developing, testing, and iterating on generative models that address real-world challenges.

What are the most commonly searched types of Generative Ai Engineer jobs in Nevada?

The most popular types of Generative Ai Engineer jobs in Nevada are:

What are popular job titles related to Generative Ai Engineer Internship jobs in Nevada?

For Generative Ai Engineer Internship jobs in Nevada, the most frequently searched job titles are:

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The top searched job categories for Generative Ai Engineer Internship jobs in Nevada are:

Generative Ai Engineer Internship jobs near you

Vice President II, Artificial Intelligence (VP of AI)

Credit One Bank

Las Vegas, NV

Full-time

Re-posted 21 days ago

Job description

Position Summary 

The Vice President of Artificial Intelligence (VP of AI) will lead enterprise-wide AI strategy, innovation, and execution. This role oversees the development, deployment, and governance of AI/ML systems across the organization, ensuring measurable business value, responsible AI practices, and alignment with corporate strategic goals. The VP of AI collaborates closely with Technology, Data, Operations, Risk, Compliance, and Business Unit leadership to build scalable AI platforms, optimize business processes, and accelerate digital transformation.

Essential Job Functions
  • Define and lead the enterprise AI strategy, including advanced analytics, machine learning, deep learning, and generative AI capabilities.
  • Build and oversee AI Centers of Excellence (CoE) to drive innovation, reusable solutions, and best practices.
  • Partner with IT, Data Engineering, and Cloud teams to establish a scalable AI/ML platform and MLOps frameworks.
  • Identify high-impact AI opportunities that drive automation, operational efficiency, customer experience improvements, and revenue growth.
  • Establish standards for Responsible AI, model governance, explainability, bias detection/mitigation, and regulatory compliance.
  • Lead the development, deployment, and lifecycle management of AI/ML models across multiple business units.
  • Oversee the creation of reusable AI components, annotation processes, model training pipelines, and evaluation frameworks.
  • Implement enterprise-wide generative AI solutions including LLMs, copilots, prompt engineering frameworks, and knowledge automation tools.
  • Collaborate with cybersecurity leaders to implement secure AI architectures, data protection controls, and model threat-defense mechanisms.
  • Promote cross-functional collaboration through transparency, communication, and evangelism of AI capabilities.
  • Build and manage high-performing AI teams including machine learning engineers, data scientists, AI product managers, and researchers.
  • Support annual planning, budgeting, strategic roadmaps, and executive-level presentations for AI programs.
  • Continuously monitor emerging AI trends, tools, and technologies and recommend adoption as appropriate.
  • Perform other duties as assigned.
Position Requirements
  • Bachelor’s degree in computer science, Engineering, Data Science, or related field. Master’s or PhD preferred.
  • 12–15+ years of progressive experience in AI/ML, software engineering, or data science, with 7+ years in leadership roles.
  • Demonstrated experience architecting, deploying, and scaling machine learning or deep learning systems in production.
  • Deep knowledge of Responsible AI frameworks, risk controls, and regulatory expectations.
  • Strong experience with cloud platforms (Azure preferred), distributed systems, and MLOps.
  • Exceptional communication skills, with ability to translate complex AI concepts for senior executives.
  • Proven ability to lead and inspire diverse technical teams.
  • Ability to drive outcomes, influence strategic decisions, and deliver business value.
  • Demonstrated alignment with company values of excellence, ownership, collaboration, and integrity.
PreferredCore AI Concepts and Technologies RequiredMachine Learning & Modeling
  • Supervised, unsupervised, reinforcement learning
  • Deep learning (CNNs, RNNs, Transformers)
  • Natural Language Processing (NLP) & LLMs
  • Generative AI (diffusion models, fine-tuning, RAG)
AI Engineering & MLOps
  • Model training, deployment, monitoring, and retraining
  • Feature stores, vector databases, and model registries
  • CI/CD pipelines for ML (MLOps)
  • GPU/accelerator compute architectures
Cloud & Infrastructure
  • Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
  • Kubernetes, containerization, microservices
  • Data platforms (Databricks, Snowflake, Synapse)
Responsible AI & Governance
  • Model explainability (SHAP, LIME)
  • Fairness, bias detection, model risk controls
  • Privacy-preserving ML techniques (differential privacy, federated learning)
Programming & Tooling
  • Python, PyTorch, TensorFlow, JAX
  • LangChain, semantic search, vector embeddings
  • Prompt engineering & LLM orchestration frameworks
Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.  
 

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