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

Do you dream in data science and machine learning models? If so, we want you to join us! Our mission is to enabletodeliver industry-winning machine learning solutions to power Micron's dominance in ...

May telecommute part-time. Employer will accept a Master's degree in Computer Science, Machine Learning, Data Science, Statistics, or related field and 3 years of experience in the job offered or in ...

As a Data Science Engineer at Micron, you will employ techniques and theories drawn from areas of ... Develop predictive models using machine learning techniques (such as regression, classification ...

As a Data Science Engineer at Micron, you will employ techniques and theories drawn from areas of ... Develop predictive models using machine learning techniques (such as regression, classification ...

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Scientific Machine Learning information

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$13

$29

$49

How much do scientific machine learning jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for scientific machine learning in Boise, ID is $29.96, according to ZipRecruiter salary data. Most workers in this role earn between $18.32 and $38.22 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Boise, ID? For Scientific Machine Learning jobs in Boise, ID, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Boise, ID look for? The top searched job categories for Scientific Machine Learning jobs in Boise, ID are:
Infographic showing various Scientific Machine Learning job openings in Boise, ID as of June 2026, with employment types broken down into 5% As Needed, 80% Full Time, 5% Part Time, 5% Contract, and 5% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $62,314 per year, or $30 per hour.

Staff Machine Learning Engineer

Micron Technology

Boise, ID • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 12 days ago


Micron Technology rating

8.8

Company rating: 8.8 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

14th of 156 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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