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Natural Language Processing Jobs in Nevada (NOW HIRING)

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Natural Language Processing (NLP) & LLMs * Generative AI (diffusion models, fine-tuning, RAG) * AI Engineering & MLOps * AI Engineering & MLOps * Model training, deployment, monitoring, and ...

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$14

$25

$49

How much do natural language processing jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for natural language processing in Nevada is $25.94, according to ZipRecruiter salary data. Most workers in this role earn between $17.88 and $30.10 per hour, depending on experience, location, and employer.

What is a natural language processing?

A Natural Language Processing (NLP) job involves developing and improving algorithms that enable computers to understand, interpret, and generate human language. Professionals in this field work on tasks like speech recognition, text analysis, machine translation, and chatbot development. They often use machine learning, deep learning, and linguistic principles to build and refine NLP models. NLP experts commonly work in industries such as healthcare, finance, and technology to enhance communication and automate language-related tasks.

What are the key skills and qualifications needed to thrive in natural language processing, and why are they important?

To thrive in Natural Language Processing, you need strong expertise in linguistics, statistics, and machine learning, typically supported by a degree in computer science, computational linguistics, or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, spaCy, and NLP libraries, as well as certifications in data science or NLP, are valuable assets. Analytical thinking, problem-solving skills, and the ability to collaborate across multidisciplinary teams are highly desirable. These competencies are essential for developing powerful language models, extracting meaningful insights from data, and delivering effective real-world solutions in language technology.

What are some typical challenges faced by professionals in natural language processing?

Professionals in Natural Language Processing (NLP) often encounter challenges such as understanding ambiguities in human language, managing large and unstructured datasets, and keeping up with rapid advances in NLP methodologies. They may also need to fine-tune models for domain-specific contexts and ensure solutions meet ethical and privacy guidelines. Collaboration with data scientists, linguists, engineers, and product teams is common, requiring strong communication skills. Successfully tackling these challenges is a critical part of developing robust NLP applications that add meaningful value to users and businesses.

How to get a job in Natural Language Processing?

To get a job in Natural Language Processing (NLP), candidates typically need a strong background in computer science, linguistics, or related fields, along with proficiency in programming languages like Python and experience with NLP libraries such as NLTK or spaCy. Gaining practical experience through projects, internships, or research, and obtaining relevant certifications can improve employability. A solid understanding of machine learning, deep learning, and data analysis is also beneficial for NLP roles.

Is natural language processing a good career?

Natural Language Processing (NLP) is a growing field within artificial intelligence that involves developing algorithms to understand and generate human language. It offers opportunities in industries such as tech, healthcare, and finance, often requiring skills in machine learning, programming, and linguistics. The demand for NLP professionals is increasing, making it a promising career choice for those interested in AI and language technologies.

What can I do with natural language processing?

A natural language processing (NLP) professional develops systems that enable computers to understand, interpret, and generate human language. This includes tasks like sentiment analysis, language translation, chatbots, and speech recognition, often using tools like Python, NLP libraries, and machine learning techniques. NLP roles require strong programming skills and knowledge of linguistics or data science.

What are the most commonly searched types of Natural Language Processing jobs in Nevada?

The most popular types of Natural Language Processing jobs in Nevada are:

What are popular job titles related to Natural Language Processing jobs in Nevada?

For Natural Language Processing jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Natural Language Processing jobs in Nevada look for?

The top searched job categories for Natural Language Processing jobs in Nevada are:

Natural Language Processing jobs near you
Infographic showing various Natural Language Processing job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, 1% Temporary, and 2% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $53,956 per year, or $25.9 per hour.

AVP, Artificial Intelligence

CreditOne

Las Vegas, NV • On-site

Full-time

Re-posted 7 days ago

Job description

Description
Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
  • Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
  • Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
  • Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
  • Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
  • Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
  • Oversee model validation, explainability, bias testing, and audit readiness.
  • Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.

Position Requirements
Core 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

  • 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

  • Excellent communication, problem-solving, and project management skills
  • Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
  • Demonstrate company core values of excellence, ownership, collaboration, and integrity.

Preferred
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
  • 5-8 + 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.

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