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Senior Machine Learning Engineer Jobs in Idaho (NOW HIRING)

Micron

Staff Machine Learning Engineer

Boise, ID · On-site

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

Bespoke Labs

Machine Learning Engineer

Nampa, ID · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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Senior Machine Learning Engineer information

See Idaho salary details

$56K

$119.1K

$172.7K

How much do senior machine learning engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for senior machine learning engineer in Idaho is $119,077.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $135,000.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for 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 Idaho?

The most popular types of Machine Learning Engineer jobs in Idaho are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Idaho?

For Senior Machine Learning Engineer jobs in Idaho, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Idaho look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Idaho are:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Idaho as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $119,077 per year, or $57.2 per hour.

Staff Machine Learning Engineer

Micron Technology

Boise, ID • On-site

$120 - $150/hr

Other

Medical, Dental, Vision, PTO

Re-posted 14 days ago

Micron Technology rating

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

27th of 160 rated electronics manufacturers

Job description

Req ID: JR101366

Staff Machine Learning Engineer

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).
Benefits

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 Benefits | Micron Technology, Inc.

Equal Opportunity Statement

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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