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Founding Machine Learning Engineer Jobs in Nevada

CTIO AI Engineering Manager

Las Vegas, NV · On-site

$73K - $244K/yr

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

$106K - $146K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques ...

NGA AI Engineer Manager

Las Vegas, NV · On-site

$73K - $244K/yr

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 ...

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 ...

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 ...

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 ...

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Founding Machine Learning Engineer information

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What engineer makes $500,000 a year?

A founding machine learning engineer at top tech companies or successful startups can earn $500,000 or more annually, often including base salary, bonuses, and equity. Such roles typically require advanced skills in deep learning, data modeling, and experience with large-scale systems, along with a strong track record of innovation and leadership.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a founding ML engineer?

A founding machine learning engineer is a key technical team member involved in building and developing the company's initial machine learning systems and infrastructure. They typically have strong skills in programming, data modeling, and deploying ML models, often working closely with product teams during the startup or early-stage company formation. This role requires a combination of technical expertise and entrepreneurial mindset to shape the company's AI capabilities from the ground up.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the increasing adoption of AI and data-driven solutions across industries. They are sought after for their skills in algorithms, programming, and tools like Python and TensorFlow, with job growth expected to continue as AI applications expand.

Which 5 jobs will survive AI?

Founding Machine Learning Engineers are likely to continue playing a crucial role as AI advances, focusing on developing and deploying complex models that require specialized skills in programming, data science, and system architecture. Jobs that involve high levels of creativity, strategic decision-making, and human interaction—such as healthcare professionals, educators, skilled trades, and roles in management—are also expected to persist despite AI automation. These positions typically require emotional intelligence, critical thinking, and adaptability that AI cannot easily replicate.

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
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What job categories do people searching Founding Machine Learning Engineer jobs in Nevada look for? The top searched job categories for Founding Machine Learning Engineer jobs in Nevada are:
What cities in Nevada are hiring for Founding Machine Learning Engineer jobs? Cities in Nevada with the most Founding 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 16 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.