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New Grad Machine Learning Jobs in Nevada (NOW HIRING)

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Physical Therapist (PT)

Las Vegas, NV · On-site

$1.5K - $2.0K/wk

New Grad Mentorship Program! * 401(k) Retirement Plan * Continuing education through an online learning portal * Industry-leading training and professional development * Employee Referral Bonus ...

Vetcor

Veterinarian - Henderson, NV

Henderson, NV · On-site

Two brand-new anesthetic machines * New dental machine and digital dental X-ray * Doppler * Two ... Peer advisors and new grad discussion groups * Case reviews and real-time support through Slack and ...

New Gig Solutions

Patent Associate

Las Vegas, NV

Participate in inventor disclosure meetings to understand the technical and business scope of new ... Cutting-edge technology portfolio -- AI, machine learning, advanced software, consumer electronics

Ormat Technologies, Inc.

Geochemist

Reno, NV

Join a team that's giving new life to the future of our planet. OverviewThis position is responsible for utilizing geochemistry to support world-class exploration, development and operations of ...

Deloitte

AI Data Engineer - Manager

Las Vegas, NV · On-site

$109K - $131K/yr

Lead the development of AI models (e.g., machine learning, natural language processing, computer ... new products. * Break down client problems and bring an understanding of leading technology ...

Maxana

Senior Technical Program Manager

$65 - $85/hr

A strong history of technical work with machine learning software and AI is required In short, you ... Exhibit the desire and ability to learn new products and technologies quickly with minimal lag time.

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All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Nevada

New Grad Machine Learning information

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How much do new grad machine learning jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for new grad machine learning in Nevada is $21.37, according to ZipRecruiter salary data. Most workers in this role earn between $13.56 and $24.81 per hour, depending on experience, location, and employer.

What are some typical challenges new graduates might face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

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

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What are 'New Grad Machine Learning' roles?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.
What are popular job titles related to New Grad Machine Learning jobs in Nevada? For New Grad Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching New Grad Machine Learning jobs in Nevada look for? The top searched job categories for New Grad Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for New Grad Machine Learning jobs? Cities in Nevada with the most New Grad Machine Learning job openings:
New Grad Machine Learning jobs near you
Infographic showing various New Grad Machine Learning job openings in Nevada as of June 2026, with employment types broken down into 1% As Needed, 54% Full Time, 37% Part Time, and 8% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,458 per year, or $21.4 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 21 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.

Apply