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Machine Learning Intern Remote Jobs in Phoenix, AZ

Relativity

Senior Applied Scientist

Phoenix, AZ · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Develop machine learning and generative AI models that ship as customer-facing product features

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Development, Machine Learning & Maintenance (30%) * Train and Test Supervised and Unsupervised ...

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Development, Machine Learning & Maintenance (30%) * Train and Test Supervised and Unsupervised ...

Phoenix Staff

Senior Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We're looking for a ... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ...

Ascend Learning

Principal AI Engineer

Gilbert, AZ · On-site +1

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Advanced understanding and practical experience in machine learning and natural language processing ...

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Showing results 1-20

All JobsMachine Learning Intern Remote JobsMachine Learning Intern Remote Jobs in Phoenix, AZ

Machine Learning Intern Remote information

See Phoenix, AZ salary details

$25.3K

$42.3K

$87.4K

How much do machine learning intern remote jobs pay per year?

As of Jun 10, 2026, the average yearly pay for machine learning intern remote in Phoenix, AZ is $42,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a remote Machine Learning Intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What does a Machine Learning Intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries for ML positions can vary based on experience, location, and company, but they tend to be above average compared to many other entry-level roles in technology. Internships in ML may offer lower pay, but full-time positions often provide competitive compensation and benefits.
What are popular job titles related to Machine Learning Intern Remote jobs in Phoenix, AZ? For Machine Learning Intern Remote jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern Remote jobs in Phoenix, AZ look for? The top searched job categories for Machine Learning Intern Remote jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Machine Learning Intern Remote jobs? Cities near Phoenix, AZ with the most Machine Learning Intern Remote job openings:
Machine Learning Intern Remote jobs near you
Infographic showing various Machine Learning Intern Remote job openings in Phoenix, AZ as of June 2026, with employment types broken down into 25% Full Time, 25% Part Time, 25% Temporary, and 25% Contract. Highlights an 100% Remote job distribution, with an average salary of $42,282 per year, or $20.3 per hour.
Senior Applied Scientist

Senior Applied Scientist

Relativity

Phoenix, AZ • On-site, Remote

Other

Medical, Retirement

Posted 17 days ago

Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE
Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical.
Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform.
At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability.
WHAT WE DO
Relativity's AI organization is focused on exploration, experimentation, and turning cutting-edge research into real-world impact. We believe innovation requires experimentation, learning, and iteration. Our teams experiment, evaluate, ship, and learn continuously while maintaining a strong commitment to responsible AI.
Applied Science Team
The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world.

Job Description and Requirements

ABOUT THE ROLE

As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence.

This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments.

WHAT YOU'LL DO

  • Develop machine learning and generative AI models that ship as customer-facing product features
  • Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle
  • Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents
  • Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems
  • Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation
  • Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance
  • Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems
  • Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development
  • Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds

WHAT WE'RE LOOKING FOR

Required

  • Experience building search or retrieval systems operating at the scale of hundreds of millions of documents
  • Experience developing and applying generative AI models as part of larger, domain-specific systems
  • Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration
  • Experience working in containerized environments using Kubernetes-based tooling and workflows
  • Interest in or experience with the legal industry, eDiscovery, or the broader justice system
  • Strong programming ability in a language such as Python
  • Comfort working in UNIX-based environments using command-line tools
  • Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders

Preferred

  • Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience
  • OR Ph.D. in Computer Science or a quantitative field
  • OR the equivalent of 5 years of relevant academic and/or industry experience
  • Experience building and deploying systems that leverage large language models
  • Experience contributing to shared data science or ML engineering standards, tooling, or best practices

WHY WE COULD BE A GREAT FIT

Impactful Mission

  • Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets.

AI at Real Scale

  • You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale.

Growth and Collaboration

  • You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems.

Responsible AI Culture

  • You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable.

Inclusive Environment

  • We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger.

Compensation and Benefits

  • Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$146,000 and $218,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models

Apply