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Machine Learning Engineer Jobs in Idaho Falls, ID

... engineering, and machine learning.We are looking for a candidate who lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts.Responsibilities · Design ...

... engineering, and machine learning. We are looking for a candidate who lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts. Responsibilities · Design ...

... engineering, and machine learning. We are looking for a candidate who lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts. Responsibilities • Design ...

Data Science Tutor

Idaho Falls, ID · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Python Tutor

Idaho Falls, ID · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Showing results 21-40

Machine Learning Engineer information

See Idaho Falls, ID salary details

$30.3K

$123.7K

$185.9K

How much do machine learning engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning engineer in Idaho Falls, ID is $123,684.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $148,900.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Idaho Falls, ID?

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

What are popular job titles related to Machine Learning Engineer jobs in Idaho Falls, ID?

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

What cities near Idaho Falls, ID are hiring for Machine Learning Engineer jobs?

Cities near Idaho Falls, ID with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Idaho Falls, ID as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $123,684 per year, or $59.5 per hour.

Cyber Analyst- Level 3

CRI Advantage

Idaho Falls, ID • Remote

$80 - $90/hr

Full-time

Posted 29 days ago


Job description

DescriptionIn this role, the selected candidate will design, build, and tune detections that identify malicious activity across our environment, working at the intersection of security analysis, data engineering, and machine learning.We are looking for a candidate who lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts.Responsibilities· Design, develop, and maintain detection content using Splunk Search Processing Language (SPL) to identify threats across diverse data sources.· Build and tune correlation searches, notable events, and risk-based alerting within Splunk Enterprise Security (ES).· Leverage the Splunk App for Data Science and Deep Learning (DSDL) to operationalize machine learning models for anomaly detection and advanced threat identification.· Apply the Splunk App for Anomaly Detection and the Splunk AI Toolkit (AITK) to develop statistical and ML-driven detections that go beyond signature-based approaches.· Map detection coverage to the MITRE ATT&CK framework and identify gaps in visibility.· Collaborate with threat intelligence, incident response, and SOC teams to translate emerging threats into actionable detections.· Reduce false positives and alert fatigue through continuous tuning and detection lifecycle management.· Develop and maintain detection-as-code workflows, including version control, testing, and CI/CD for detection content.· Create documentation, runbooks, and detection specifications to support downstream analysts.Requirements· Have a current "L" , "Q" or "TS" clearance.· Have the following required skillsets:o Deep expertise in Splunk SPL, including advanced search commands, statistical functions, data models, and performance optimization.o Hands-on experience with Splunk Enterprise Security, including correlation searches, risk-based alerting (RBA), notable events, and the ES framework.o Working knowledge of the Splunk AI Toolkit (AITK) for building and applying ML-based detections.o Experience with the Splunk App for Data Science and Deep Learning (DSDL), including custom model development and deployment.o Strong understanding of the MITRE ATT&CK framework and detection engineering methodology.o Familiarity with common attack techniques, log sources, and security data (EDR, network, cloud, identity, etc.).Preferred Qualifications · Experience with detection-as-code practices and tools (Git, CI/CD pipelines).· Proficiency in Python for data processing and model development.· Knowledge of SOAR platforms and detection automation.· Relevant certifications (Splunk Certified Power User/Admin, Splunk Enterprise Security Certified Admin, GIAC, etc.).· Prior experience in a SOC, threat hunting, or incident response role.