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Machine Learning Engineer Jobs in Boise, ID (NOW HIRING)

Micron

Gas Systems Engineer - O&M

Boise, ID · On-site

The engineer leverages data analytics, AI-enabled tools, and digital technologies to enhance ... Utilize AI, machine learning, and advanced analytics tools to identify trends, predict equipment ...

New

Micron Technology

Gas Systems Engineer - O&M

Boise, ID · On-site

The engineer leverages data analytics, AI-enabled tools, and digital technologies to enhance ... Utilize AI, machine learning, and advanced analytics tools to identify trends, predict equipment ...

VELOX

GTM Engineer (AI Sales & Engineering)

Boise, ID · On-site

The AI Developer will be responsible for streamlining AI integrations with several existing ... The ideal candidate will have extensive experience working with AI, machine learning, and large ...

VELOX

GTM Engineer (AI Sales & Engineering)

Boise, ID · On-site

The AI Developer will be responsible for streamlining AI integrations with several existing ... The ideal candidate will have extensive experience working with AI, machine learning, and large ...

Micron

Staff Engineer, CE CAD

Boise, ID · On-site

$106K - $267K/yr

Explore and apply generative AI and machine learning techniques to practical custom IC design and ... Strong programming skills in Python, experience developing maintainable technical software or ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Boise, ID

Machine Learning Engineer information

See Boise, ID salary details

$30K

$122.6K

$184.2K

How much do machine learning engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning engineer in Boise, ID is $122,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,600.00 and $147,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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.

More about Machine Learning Engineer jobs

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Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Boise, ID as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $122,560 per year, or $58.9 per hour.

Product Yield & Analytics PYAi Engineer

Micron Technology, Inc

Boise, ID • On-site

$90 - $120/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Micron Technology rating

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

26th of 161 rated electronics manufacturers

Job description

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

We are seeking a highly motivated Senior Data Science & Product Yield Analytics Engineer to join the Product Yield & Analytics (PYA) organization. This role focuses on applying data science, software engineering, and advanced analytics to semiconductor manufacturing data, with a strong emphasis on Improved Software for Defect Analysis (ESDA) and Electrical Failure Analysis bench testing systems used companywide.

In this position, you will employ techniques drawn from statistics, machine learning, semiconductor physics, and large-scale data engineering to uncover patterns, build predictive models, and develop actionable insights that drive yield, quality, and reliability improvements across Micron’s memory products.

You will work closely with Data Scientists, Data Engineers, Product Engineers, Build teams, Yield Enhancement, RDA, Failure Analysis, and IT teams across global sites to develop and expand ESDA capabilities and analytics platforms that directly support manufacturing and product development.

Responsibilities:
  • Expand and enhance ESDA capabilities to improve yield, quality, and product reliability.
  • Develop yield, defect matching, and modeling methods to accelerate manufacturing feedback to RDA and YE teams.
  • Create and maintain engineering software tools for ESDA analytics and product line monitoring.
  • Collaborate with design, failure analysis, and product teams to optimize redundancy, compression, and defect analysis methodologies.
  • Support next-generation memory devices through advanced analytics and data-driven insights.
  • Using AI in applicable job functions.
Minimum Qualifications:
  • BS or MS in Electrical Engineering, Computer Engineering, Data Science, Software Development, or a related technical field.
  • Proficiency in at least one programming language and familiarity with machine learning and data science techniques.
  • Familiarity with Micron’s Improved Software for Defect Analysis (ESDA) system.
Preferred Qualifications:
  • Experience with memory products in product engineering, test, build, yield improvement, software development, or data science.
  • Strong analytical and problem-solving skills applied to sophisticated manufacturing data.
  • Ability to communicate complex technical concepts effectively across global, multi-functional teams.

Job Profile(s): Product Development Engineer 3 - Product Development Engineer 4

Relocation Level: TBD

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

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