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Machine Learning Engineer Opt Jobs in Caldwell, ID

As a Principal Machine Learning Engineer, willhave experiencein a variety of dataand cloudtechnologies and have extensive practice modeling data, querying, anddeployingscalable pipelinestoexecute ...

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 ...

... 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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Showing results 1-20

Machine Learning Engineer Opt information

See Caldwell, ID salary details

$28.4K

$115.9K

$174.2K

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

As of Aug 19, 2026, the average yearly pay for machine learning engineer opt in Caldwell, ID is $115,918.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,400.00 and $139,500.00 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What cities near Caldwell, ID are hiring for Machine Learning Engineer Opt jobs?

Cities near Caldwell, ID with the most Machine Learning Engineer Opt job openings:

Infographic showing various Machine Learning Engineer Opt job openings in Caldwell, ID as of August 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $115,918 per year, or $55.7 per hour.

Principal Machine Learning Engineer

Micron Technology, Inc

Boise, ID • On-site

$150 - $210/hr

Other

Medical, Dental, Vision, PTO

Posted 8 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 159 rated electronics manufacturers


Job description

Req ID: JR106544 Principal 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! As a Principal Machine Learning Engineer, 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:
  • Design, build, and continuously refine ML models to address business challenges and enhance product capabilities.
  • Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models.
  • 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 implement Generative AI integration strategies and roadmaps.
  • Communicate insights and collaborate multi-functionally, translating complex analytics into actionable recommendations for diverse collaborators.
  • Drive the technical vision and lead end-to-end execution of complex, multi-functional AI/ML projects.
  • Mentor and coach developing and senior team members, elevating the overall technical competence of the engineering team.
  • Embrace and champion AI-assisted software development such as Opencode, Copilot; while strictly managing and auditing AI agents to ensure production quality code that is reliable, secure and high quality.
Minimum Qualifications:
  • Master's or PhD degree in Computer Science, Machine Learning, Data Science, Statistics, or a field closely related to AI and Machine Learning with 8+ years (or PhD with 5+ years) experience building end-to-end ML systems on cloud platforms, automating model training, testing, and deployment.
  • Strong experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) 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.
  • Proven track record of technical leadership, including leading ML project delivery and mentoring engineering teams.
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.
  • Advanced experience using and managing GenAI coding assistants, with a strong ability to peer-review and rigorously test AI-generated code logic.
  • Hands-on experience building Generative AI solutions and intelligent agents (ADK, LangChain/LangGraph, CrewAI, DsPy, Semantic Kernel).
  • 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) and MLOps/CE platforms (MLflow, Kubeflow, Vertex AI, SageMaker, TFX)
Job Profile(s):

Machine Learning Engineer 5

Relocation Level: TBD

Before Getting Started

Please review Micron’s Internal Job Application Policy on your regional PeopleNow Career Opportunities page before searching and applying for jobs. Note in particular that:

  • Hiring managers may view your performance appraisals, original resume, transcripts or other performance-related documentation in your personal file. This information will be held in confidence.
  • If you are selected to interview for a position, you must notify your direct supervisor before participating in the interview process.
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.

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 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)

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