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

Machine Learning Engineer Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Senior AI/ML Engineer

Boise, ID · Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

Data Analyst V

Boise, ID · Remote

$130K/yr

USA Remote Responsibilities * Work with large and complex datasets to solve challenging problems ... Apply advanced statistical modeling, machine learning, and natural language processing (NLP) to ...

Senior AI/ML Engineer

Boise, ID · On-site +1

$99K - $136K/yr

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... Experience with computer vision , machine learning , or data-centric AI projects - especially where ...

... remote work and setting your own schedule. We are looking for a proficient Coder (part-time work ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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Remote Machine Learning information

See Boise, ID salary details

$24.3K

$40.5K

$83.8K

How much do remote machine learning jobs pay per year?

As of Jun 9, 2026, the average yearly pay for remote machine learning in Boise, ID is $40,529.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,900.00 and $43,800.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.
What are the most commonly searched types of Machine Learning jobs in Boise, ID? The most popular types of Machine Learning jobs in Boise, ID are:
What are popular job titles related to Remote Machine Learning jobs in Boise, ID? For Remote Machine Learning jobs in Boise, ID, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Boise, ID look for? The top searched job categories for Remote Machine Learning jobs in Boise, ID are:
Machine Learning Engineer

Machine Learning Engineer

Equifax

Boise, ID • On-site, Remote

Other

Medical, Retirement, PTO

Posted 6 days ago


Equifax rating

7.8

Company rating: 7.8 out of 10

Based on 21 frontline employees who took The Breakroom Quiz


Job description

Machine Learning Engineer

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

As a Machine Learning Engineer in the Identity and Fraud business at Equifax, you will solve challenging technology problems and build architecturally sound, high-quality software that moves data through models to make automated decisions. You will achieve success through communicating, collaborating, and developing creative and performant solutions to help Equifax provide certainty in every digital transaction for our customers. You should be a creative, driven, motivated engineer that can think outside the box, has the ability to learn quickly, and can deliver high-quality working solutions that are both maintainable and scalable. You will work with data scientists to develop requirements for novel algorithms, and with operations and other developers to bring data transformation pipelines and machine learning models to practice.

What You'll Do
  • Design platforms and pipelines for researching, developing, and running machine learning models
  • Productionize machine learning models by building performant data transformations, storage, and pipelines
  • Develop and maintain microservices that serve data, model features, and scores to other internal services, as well as external customers
  • Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross-functional team consisting of Data Science, Operations, and Engineering
  • Apply development and testing best practices (including unit, service, and integration tests) and demonstrate excellent software craftsmanship to produce maintainable, scalable, and quality solutions.
  • Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment.
  • Deliver on company initiatives and projects prioritized for your team and support long term technical vision.
  • Collaborate with the product team, architects, and others to document features and changes.
  • Identify gaps and iterative improvements to legacy model platforms, frameworks, or governance stacks
  • Adhere to and influence best practices (i.e. security, architecture, platform, etc.)
  • Participate in peer design and code reviews
  • Participate in on-call rotation with other engineers
What Experience You Need
  • BS in Computer Science, Engineering, or equivalent experience.
  • 3+ years of strong software engineering and software architecture background using languages such as Golang, Python, and SQL.
  • 3+ years of experience building RESTful APIs and/or gRPC within a distributed microservice architecture.
  • 2+ years of experience implementing Amazon Web Services (e.g., IAM, Lambda, EKS, Neptune, DynamoDB, RDS).
  • 2+ years of experience using IaC tooling such as Terraform
  • Experience working with machine learning frameworks such as SparkMLlib, Scikit-Learn, MLflow, or TensorFlow.
  • Experience serving ML model inference at scale in low-latency (<30ms) environments.
  • Experience with metrics, logging, and evaluating model performance (e.g., DataDog, evaluation latency, and ROC curves).
What Could Set You Apart
  • Experience with Snowflake
  • Experience with AWS EMR
  • Experience deploying diverse model architectures into production using portable formats like ONNX or MLeap.

We offer comprehensive compensation and healthcare packages, 401k matching, paid time off, and organizational growth potential through our online learning platform with guided career tracks.

Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!

Primary Location: USA-ID-Boise

Function: Tech Dev and Client Services

Schedule: Full time


What Equifax employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Equifax

Sourced by ZipRecruiter

As a global data, analytics, and technology company, we play an essential role in the economy by helping companies in diverse industries such as automotive, communications, utilities, financial services, fintech, healthcare, insurance, mortgage, professional services, retail, e-commerce, and government agencies, make critical decisions with greater confidence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

Year founded

1899

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