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Deep Learning Jobs in Nevada (NOW HIRING)

Lead Artificial Intelligence Engineer

Las Vegas, NV · On-site

$99K - $130K/yr

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 ...

Manager, Learning and Development

Las Vegas, NV

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Enterprise Learning Strategy & Function Leadership. Lead and architect the end-to-end Learning ... Deep expertise in performance management, manager enablement, and organizational effectiveness.

Deep learning (CNNs, RNNs, Transformers) * Natural Language Processing (NLP) & LLMs * Generative AI (diffusion models, fine-tuning, RAG) * AI Engineering & MLOps * AI Engineering & MLOps * Model ...

Showing results 21-40

Deep Learning information

See Nevada salary details

$11.2K

$85.4K

$142.6K

How much do deep learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for deep learning in Nevada is $85,421.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,300.00 and $141,500.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a deep learning professional?

As a Deep Learning professional, your day-to-day tasks often include designing and training neural network models, preprocessing and analyzing large datasets, and evaluating model performance using various metrics. You may also participate in research activities, document your results, and collaborate with data scientists, engineers, or product teams to deploy machine learning solutions. Regular meetings for project updates, code reviews, and brainstorming sessions are common, as is staying updated on advances in the field. This dynamic environment offers both individual and team-based work, providing continuous learning and the opportunity to solve complex, real-world problems.

What is a deep learning job?

A Deep Learning job involves designing, developing, and optimizing neural networks to solve complex problems such as image recognition, natural language processing, and autonomous systems. Professionals in this field work with large datasets, neural network architectures, and frameworks like TensorFlow or PyTorch. They collaborate with data scientists, engineers, and researchers to improve model accuracy and efficiency. Deep Learning roles typically require strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration.

What are the key skills and qualifications needed to thrive in a deep learning position?

To thrive in Deep Learning, you need a solid understanding of machine learning theory, neural networks, mathematics (especially linear algebra and probability), and programming skills, typically backed by a degree in computer science, mathematics, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with data preprocessing, and optionally industry-recognized certifications are advantageous. Strong analytical thinking, problem-solving skills, and the ability to communicate findings clearly are crucial soft skills. These abilities enable the design, implementation, and optimization of effective deep learning solutions in real-world applications.

What are the most commonly searched types of Deep Learning jobs in Nevada?

The most popular types of Deep Learning jobs in Nevada are:

What are popular job titles related to Deep Learning jobs in Nevada?

For Deep Learning jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Deep Learning jobs?

Cities in Nevada with the most Deep Learning job openings:

Infographic showing various Deep Learning job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $85,421 per year, or $41.1 per hour.

Vice President II, Artificial Intelligence (VP of AI)

Credit One Bank

Las Vegas, NV

Full-time

Re-posted 19 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.