1

Artificial Intelligence Machine Learning Engineer Jobs in Nevada

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier ...

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier ...

... on artificial intelligence engineering to build and deploy AI and machine learning-based solutions at scale. As a Manager, you will lead teams and manage client accounts, focusing on strategic ...

New

... Artificial Intelligence and Robotics preferred - Designing, training, and deploying machine ... learning models - Developing scalable, cloud-native microservices using Docker and Kubernetes ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Reno, NV · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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 ... Artificial Intelligence and Robotics preferred - Demonstrating exceptional team leadership ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Engineering, Artificial Intelligence and Robotics preferred - Crafting and conveying clear ...

next page

Showing results 1-20

Artificial Intelligence Machine Learning Engineer information

See Nevada salary details

$32.1K

$131.1K

$197K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for artificial intelligence 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 an Artificial Intelligence Machine Learning Engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by Artificial Intelligence Machine Learning Engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior AI or machine learning engineers, research directors, or executive positions in artificial intelligence. These roles often require advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch, along with leadership responsibilities and a strong track record of innovation. Compensation at this level reflects extensive expertise, strategic impact, and often involves stock options or bonuses in addition to base salary.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What engineers make $500,000?

Artificial Intelligence and Machine Learning Engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and work in high-demand industries like tech or finance. Compensation often includes base salary, bonuses, and stock options, particularly at senior levels or in leadership roles.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

Is AI ML engineer in demand?

AI and ML engineers are in high demand across various industries due to the increasing adoption of artificial intelligence technologies. Companies seek professionals skilled in programming languages like Python, machine learning frameworks, and data analysis to develop and implement AI solutions, leading to strong job growth and competitive salaries in this field.

How much do AI ML engineers make?

AI ML engineers typically earn a median salary ranging from $100,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in deep learning, natural language processing, or cloud platforms can command higher salaries, often exceeding $200,000.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Nevada? For Artificial Intelligence Machine Learning Engineer jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Nevada look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Nevada are:
What cities in Nevada are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities in Nevada with the most Artificial Intelligence Machine Learning Engineer job openings:
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Nevada as of June 2026, with employment types broken down into 86% Full Time, 9% Part Time, 3% Contract, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $131,126 per year, or $63 per hour.
Machine Learning Engineer- AI Data Platform (Reno, NV)

Machine Learning Engineer- AI Data Platform (Reno, NV)

MOBE, LLC

Reno, NV

$114K - $137K/yr

Full-time

Posted 20 days ago


Job description

Company Overview

MOBE helps people discover new ways to live healthier. We are the whole-person, cross-condition solution that goes further to deliver better health and lower overall costs through evidence-based individual health guidance and pharmacist-led medication management. We empower individuals to make meaningful changes that improve their health and overall well-being. Behind our innovative solutions are robust data analytics, digital application, and a uniquely human philosophy. With one-to-one connection and compassion, we uncover opportunities, overcome challenges, and motivate people to transform their lives.

At MOBE our team is our most significant asset. We cultivate a culture grounded in curiosity, innovation, and growth. We encourage new ideas, fresh solutions, and meaningful impact. We value a workforce made up of people with differences who are eager to learn from each other and grow personally and professionally. We extend this approach to our partners and communities, seeking to increase understanding and expand opportunities across all groups.

Your role at MOBE

We are seeking a highly skilled AI Engineer to serve as a core builder of our AI Data Platform. This role sits at the intersection of machine learning engineering, data platform development, and business intelligence, with responsibility for designing and operating the infrastructure that powers AI-driven insights across the organization.

You will build intelligent data pipelines, production-grade ML systems, and AI-enabled features that translate complex data into actionable outcomes. This role is ideal for an engineer who enjoys working end-to-end from data ingestion and feature engineering to model deployment and downstream consumption in analytics and BI tools.

**Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Responsibilities:

  • Build AI-first data pipelines: Design, implement, and maintain scalable data pipelines that support model training, inference, and analytics use cases across the AI Data Platform.
  • Deploy production ML systems: Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability, observability, and performance in production environments.
  • Implement Retrieval-Augmented Generation (RAG): Architect and maintain RAG-based systems that combine structured and unstructured data to power AI-driven insights and applications.
  • Operationalize ML lifecycle management: Use MLflow for experiment tracking, model versioning, and lifecycle management to support reproducibility and continuous improvement.
  • Design feature infrastructure: Build and manage feature stores (e.g., Feast, Tecton, or SageMaker Feature Store) to ensure consistent, reusable features across training and inference.
  • Orchestrate complex workflows: Create and manage Apache Airflow DAGs to orchestrate data transformations, model pipelines, and AI workflows with clear dependencies and monitoring.
  • Enable analytics consumption: Partner with BI and analytics teams to ensure ML outputs integrate cleanly with our internal BI reporting hub.
  • Translate business questions into AI solutions: Collaborate with stakeholders to convert ambiguous business problems into measurable ML- and data-driven solutions.
  • Uphold data quality and governance: Ensure AI pipelines and models adhere to data governance, security, and quality standards, particularly when handling sensitive data.
  • Collaborate cross-functionally: Work closely with Data Science, Analytics Engineering, Medical Economics, and DataOps to align AI platform capabilities with business priorities.