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Vice President Process Improvement Engineer Jobs in Nevada

Job Overview The VP of Data & Analytics is the senior leader responsible for AGS's entire data ... Strong data engineering foundations - deep enough technical understanding to review architecture ...

The Vice President will lead a team of Product Analysts and serve as the primary liaison between ... Bachelor's degree in Business, Information Systems, Technology, Engineering, Finance, or related ...

The Vice President will lead a team of Product Analysts and serve as the primary liaison between ... Bachelor's degree in Business, Information Systems, Technology, Engineering, Finance, or related ...

The Vice President will lead a team of Product Analysts and serve as the primary liaison between ... Bachelor's degree in Business, Information Systems, Technology, Engineering, Finance, or related ...

Finally, the VP/SVP of F&B must foster an environment of continuous improvement and ensure that ... Knowledge and understanding of pre-opening processes. * Financial acumen with experience in budget ...

The Vice President will lead a team of Product Analysts and serve as the primary liaison between ... Bachelor's degree in Business, Information Systems, Technology, Engineering, Finance, or related ...

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Vice President Process Improvement Engineer information

What is the difference between Vice President Process Improvement Engineer vs Process Improvement Manager?

AspectVice President Process Improvement EngineerProcess Improvement Manager
ResponsibilitiesStrategic leadership, setting company-wide process improvement goalsImplementing and managing specific process projects
Experience & CredentialsAdvanced degree, extensive industry experience, leadership skillsRelevant certifications, several years of process improvement experience
Work EnvironmentExecutive-level meetings, cross-departmental strategyProject teams, operational departments
Industry UsageCommon in large corporations, manufacturing, and tech firmsWidely used across industries for operational efficiency

The Vice President Process Improvement Engineer focuses on strategic, high-level process improvements and leadership, while the Process Improvement Manager handles day-to-day project execution and team management. Both roles require relevant certifications and experience, but the VP role emphasizes strategic vision and cross-departmental influence.

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Cities in Nevada with the most Vice President Process Improvement Engineer job openings:

Vice President II, Artificial Intelligence (VP of AI)

Credit One Bank

Las Vegas, NV • On-site

Full-time

Re-posted 10 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.