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

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Collaborate on data preprocessing and feature engineering to enhance the quality of input data for machine learning models. Build custom software components and analytics applications. Create ...

... DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills. Preferred Qualifications: * Strong foundation in machine learning and ...

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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 Jul 3, 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 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 Boise, ID? The most popular types of Machine Learning Engineer jobs in Boise, ID are:
What are popular job titles related to Machine Learning Engineer jobs in Boise, ID? For Machine Learning Engineer jobs in Boise, ID, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Boise, ID look for? The top searched job categories for Machine Learning Engineer jobs in Boise, ID are:
What cities near Boise, ID are hiring for Machine Learning Engineer jobs? Cities near Boise, ID with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Boise, ID as of June 2026, with employment types broken down into 1% As Needed, 93% Full Time, 4% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $122,560 per year, or $58.9 per hour.
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Micron Technology

Boise, ID • On-site

Full-time

Medical, Dental, Vision, PTO

Posted 13 days ago


Micron Technology rating

8.7

Company rating: 8.7 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

11th of 141 rated electronics manufacturers


Job description

Our vision is to transform how the world uses information to enrich life for all.
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.
The Smart Manufacturing and AI team at Micron Technology is looking for an ambitious Machine Learning Engineer. Are you curious, high velocity, and ready to solve complex problems? Do you dream in data science and machine learning models? If so, we want you to join us!
Our mission is to enable to deliver industry-winning machine learning solutions to power Micron's dominance in the highly competitive memory solutions market. Qualified applicants will have experience in a variety of data and cloud technologies and have extensive practice modeling data, querying, and deploying scalable pipelines to execute machine learning models. You will collaborate with Data Scientists, ML Engineers, Data Engineers, and expert users to build and deploy scalable AI/ML solutions that drive value and insight from Micron's manufacturing processes and systems.
Responsibilities:
  • Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models.
  • Design, build, and continuously refine ML models to address business challenges and enhance product capabilities.
  • Stay ahead of advancements in AI/ML and integrate emerging techniques into the MLOps lifecycle.
  • Build and maintain robust, scalable data pipelines and infrastructure to support model training and deployment.
  • Collaborate on data preprocessing and feature engineering to improve input data quality and model performance.
  • Design and optimize data architectures across cloud platforms (Snowflake, GCP, Azure) for AI/ML use cases.
  • Develop custom applications and implement CI/CD pipelines to support efficient ML solution deployment.
  • Deploy, evaluate, and monitor models in production, balancing performance with cost efficiency and enabling continuous improvement.
  • Partner with Product and Engineering teams to define and execute Generative AI integration strategies and roadmaps.
  • Communicate insights and collaborate multi-functionally, translating complex analytics into actionable recommendations for diverse collaborators.

Minimum Qualifications:
  • Master's degree in Computer Science, Machine Learning, Data Science, Statistics, or a field closely related to AI and Machine Learning with 3+ years building end-to-end ML systems on cloud platforms, automating model training, testing, and deployment.
  • Strong experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and core techniques including regression, classification, deep learning, reinforcement learning, and generative AI.
  • Proficient in Python or Java, with experience developing APIs and event-driven pipelines using Kafka, Pub/Sub, or similar messaging systems.
  • Skilled in scalable data engineering, including ETL/ELT pipelines (Kubeflow, Airflow, Dataflow), SQL, and data architecture design.
  • Hands-on experience with cloud and DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills.

Preferred Qualifications:
  • Strong foundation in machine learning and deep learning, with solid grounding in probability and statistics.
  • Proven ability to productionize data science prototypes into scalable, real-world solutions.
  • Hands-on experience building Generative AI solutions and intelligent agents (LangChain/LangGraph, CrewAI, DsPy, Semantic Kernel, ADK).
  • Expertise in semantic search and retrieval systems, including RAG, GraphRAG, NLP, prompt engineering, and LLM fine-tuning/evaluation.
  • Experience with end-to-end data and engineering workflows: ETL pipelines, big data processing, databases (BigQuery, Snowflake, MSSQL, PostgreSQL), and CI/CD tools (Git, Docker, Kubernetes, Jenkins).

As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits.
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.
To learn about your right to work click here.
To learn more about Micron, please visit micron.com/careers
For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at hrsupport_na@micron.com or 1-800-336-8918 (select option #3)
Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.
Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.
AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.
Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

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