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Machine Learning Engineer Jobs in Reno, NV (NOW HIRING)

SDLC Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

SDLC Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

QA Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

QA Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

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Showing results 1-20

Machine Learning Engineer information

See Reno, NV salary details

$31.4K

$128.4K

$192.9K

How much do machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer in Reno, NV is $128,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $154,500.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Reno, NV? The most popular types of Machine Learning Engineer jobs in Reno, NV are:
What are popular job titles related to Machine Learning Engineer jobs in Reno, NV? For Machine Learning Engineer jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Reno, NV look for? The top searched job categories for Machine Learning Engineer jobs in Reno, NV are:
What cities near Reno, NV are hiring for Machine Learning Engineer jobs? Cities near Reno, NV with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Reno, NV as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,391 per year, or $61.7 per hour.

$58.83 - $82.37/hr

Full-time

Posted 6 days ago


Job description

Job Title: Data Engineer
Location: Reno, NV (Remote or Hybrid)
Salary Range: $58.83-$82.37 per hour

Primary Responsibilities:

  • Experience with AWS infrastructure including AWS Connect and AWS Lambda.
  • Manage and optimize the movement and validation of data from an Epic EMR system to SQL databases in AWS or Azure and either from or to the Salesforce platform.
  • Accountable for data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance.
  • Oversee the development of novel data pipelines that integrate and normalize large data from a variety of sources to enable learning health, machine learning model development, and deployment.
  • Design, direct, and implement ETL processes, including data capture, data quality, testing, and validation methods.
  • Layer in instrumentation in the development process so that data pipelines can be monitored.
  • Build processes and diagnostic tools to troubleshoot, maintain, and optimize engineering environments and respond to production issues.
  • Provide subject matter expertise and hands-on delivery of data capture, curation, and consumption pipelines for AWS.
  • Participate in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the Azure platform.
  • Develop documentation, such as data dictionaries, guides, or data flow diagrams that assist staff in identifying, locating, and using the organizations data.

Incumbent Must Possess:

  • Minimum of 3 years of SQL programming experience and associated SQL tools (SSIS, SSMS, SSRS, etc.).
  • Experience with Visual Studio is preferred.
  • At least 3 years of experience in developing data ingestion, data processing, and analytical pipelines for big data, relational databases, NoSQL, and data warehouse solutions.
  • Minimum of 3 years of RDBMS experience.
  • Extensive hands-on experience implementing data migration and data processing using Amazon Web Services. Includes knowledge of Amazon Connect and Amazon Lambda.
  • Knowledge of medical terminology, especially ICD-10 codes, CPT codes, DRG codes, and an understanding of adjudicated claims data.
  • Excellent verbal and written communication skills.

Minimum Qualifications:

  • Education: Masters degree with 10 years experience preferred; Bachelors degree with 13 years of equivalent experience will be considered in place of masters degree requirement.
  • Experience: Requires a minimum of 10 years experience with at least five (5) years working in data management, data engineering, or data architecture. Enterprise Data Warehouse development preferred; Requires at least five (5) years working with healthcare data; more is preferred. SQL proficiency is required.
  • License(s): None
  • Certification(s): Certification work related to Epic or Amazon Cloud may be required within 1 year of starting employment.
  • Computer / Typing: Must be proficient with Microsoft Office Suite, including Outlook, PowerPoint, Excel, and Word and can use the computer to complete online learning requirements for job-specific competencies, access online forms and policies, complete online benefits enrollment, etc.

This role offers a unique opportunity to work on cutting-edge data engineering projects in the healthcare industry. If you meet the qualifications and are excited about the potential of this role, we encourage you to apply.