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Generative Ai Training Jobs in Nevada (NOW HIRING)

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 ...

Pwc

AI Engineer

Las Vegas, NV · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... training and/or progressively responsible work experience in Engineering with AI and Machine ... Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning ...

Deloitte

Cyber - AWS Cloud Security - Manager

Las Vegas, NV · On-site

$106K - $143K/yr

Experience securing machine learning, generative AI, or agentic AI workloads and pipelines on AWS ... and training; licensure and certifications; and other business and organizational needs. The ...

Pwc

US Tech - AI Engineering Senior Associate

Las Vegas, NV · On-site

$55K - $187K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... and validate Generative AI agents and data pipelines, promoting reliability, scalability, and ... training in technology preferred - Experience with test automation and CI/CD pipelines ...

Deloitte

Deployment Success Manager

Las Vegas, NV

... Generative AI, transformative technologies, and creative design. We can enhance customer ... and training; licensure and certifications; and other business and organizational needs. The ...

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Generative Ai Training information

What is generative AI training?

Generative AI training refers to the process of teaching artificial intelligence models, such as neural networks, to create new content like text, images, audio, or code. This is done by exposing the AI to large datasets so it can learn underlying patterns and generate outputs that mimic human-like creativity. The training process often involves techniques like supervised learning, unsupervised learning, or reinforcement learning, depending on the desired outcome. Generative AI is widely used in applications like chatbots, image generation, and content creation.

What are the key skills and qualifications needed to thrive in generative AI training?

To thrive in Generative AI Training, you need a strong background in machine learning, data science, and programming (especially Python), often supported by a degree in computer science or a related field. Experience with frameworks like TensorFlow, PyTorch, and familiarity with large language models and cloud platforms is typically required. Strong analytical thinking, creativity, and effective communication are essential soft skills for designing training data and refining model outputs. These skills and qualities are crucial for developing high-quality, ethical, and scalable AI systems that meet organizational goals.

What are some common challenges faced by professionals working in generative AI training roles?

Professionals in Generative AI training often encounter challenges such as ensuring data quality and diversity, combating model bias, and staying updated with fast-evolving algorithms. Collaborating closely with data scientists, engineers, and subject matter experts is essential to create robust training datasets and refine model outputs. Additionally, balancing computational resource demands with project deadlines can be demanding, making strong project management and adaptability key assets in this role.

What is the difference between Generative Ai Training vs Data Scientist?

AspectGenerative Ai TrainingData Scientist
Required CredentialsKnowledge of AI models, programming, machine learningStatistics, programming, data analysis
Work EnvironmentAI development teams, tech companies, research labsBusiness, finance, tech firms, research institutions
Industry UsageDeveloping generative models like GPT, DALL·EData analysis, predictive modeling, insights generation

Generative Ai Training focuses on developing and fine-tuning AI models that generate content, requiring expertise in AI frameworks and machine learning. Data Scientists analyze data to extract insights and build predictive models. While both roles involve programming and data skills, Generative Ai Training is specialized in AI model creation, whereas Data Scientists work broadly with data analysis across industries.

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

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

What job categories do people searching Generative Ai Training jobs in Nevada look for?

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

Generative Ai Training jobs near you
Infographic showing various Generative Ai Training job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Lead Artificial Intelligence Engineer

Credit One Bank

Las Vegas, NV

$99K - $130K/yr

Full-time

Re-posted 22 days ago

Job description

Position Summary

The Lead Artificial Intelligence Engineer develops and produces AI and machine learning solutions supporting banking and credit card businesses. This role focuses on building scalable, explainable, and compliant AI models for fraud detection, credit risk, customer analytics, and operational intelligence.

Essential Job Functions
  • Develop, train, and optimize ML, deep learning, and Generative AI models.
  • Implement data pipelines, feature engineering, and model inference services.
  • Deploy and monitor models using enterprise MLOps practices.
  • Support model explainability, bias analysis, and regulatory documentation.
  • Collaborate with data engineers, risk, and compliance teams.
Position RequirementsCore AI Concepts and Technologies Required:
  • Machine 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
Preferred
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
  • 3–7 years of experience in AI/ML or data science.
  • Experience working with large-scale financial or transactional data is preferred.
 
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.