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Quantum Machine Learning Engineer Jobs in Nevada

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Sr AI/ML Engineer

Sparks, NV · On-site

$106K - $146K/yr

Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques ... Exposure to or interest in quantum computing for ML applications. Essential Functions: * Contribute ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Senior Embedded Software Engineer

Las Vegas, NV · On-site +1

$118K - $155K/yr

Motional's onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional's next-generation on ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Machine Learning & Modeling * Supervised, unsupervised, reinforcement learning * Deep learning ... AI Engineering & MLOps * AI Engineering & MLOps * Model training, deployment, monitoring, and ...

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Linear Algebra Tutor

Las Vegas, NV · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Linear Algebra Tutor

Reno, NV · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Lead Data Engineer

Las Vegas, NV · On-site

$121K - $162K/yr

Support AI, machine learning, Generative AI, and RAG solutions through scalable data engineering, feature engineering, and MLOps/DataOps practices. * Implement modern engineering standards, including ...

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Quantum Machine Learning Engineer information

See Nevada salary details

$32.1K

$131.1K

$197K

How much do quantum machine learning engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for quantum machine learning engineer in Nevada is $131,126.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $157,800.00 per year, depending on experience, location, and employer.

What is the salary of quantum machine learning engineer?

The salary of a quantum machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in quantum algorithms and programming languages like Python or Qiskit may offer higher compensation. Many positions also include benefits such as research opportunities and access to advanced quantum computing tools.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum hardware. The field is emerging, with high demand for specialized skills in quantum algorithms, programming languages like Qiskit, and understanding of both quantum physics and data science. Careers in this area can be rewarding but often require advanced education and continuous learning due to rapid technological advancements.

What is a Quantum Machine Learning Engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

Will MLE be replaced by AI?

Quantum Machine Learning Engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum systems. While AI continues to advance, quantum computing is expected to complement classical machine learning rather than replace it entirely, and MLE roles will evolve to incorporate new quantum techniques and tools. Continuous learning in both quantum algorithms and machine learning is essential for professionals in this field.

How do Quantum Machine Learning Engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

What are the key skills and qualifications needed to thrive as a Quantum Machine Learning Engineer, and why are they important?

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.
What are popular job titles related to Quantum Machine Learning Engineer jobs in Nevada? For Quantum Machine Learning Engineer jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Quantum Machine Learning Engineer jobs in Nevada look for? The top searched job categories for Quantum Machine Learning Engineer jobs in Nevada are:
What cities in Nevada are hiring for Quantum Machine Learning Engineer jobs? Cities in Nevada with the most Quantum Machine Learning Engineer job openings:
Vice President II, Artificial Intelligence (VP of AI)

Vice President II, Artificial Intelligence (VP of AI)

Credit One Bank

Las Vegas, NV

Full-time

Re-posted 18 days ago


Job description

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.