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Internship Applied Scientist Machine Learning Jobs in Phoenix, AZ

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Principal Data Scientist

Phoenix, AZ · On-site

$150 - $210/hr

Design machine learning workflows using Azure Machine Learning, including experimentation, model ... Applied ML Depth: Strong foundation in predictive modeling, NLP, classification, regression ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

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Internship Applied Scientist Machine Learning information

See Phoenix, AZ salary details

$25.3K

$42.3K

$87.4K

How much do internship applied scientist machine learning jobs pay per year?

As of Aug 30, 2026, the average yearly pay for internship applied scientist machine learning 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 does an internship applied scientist in machine learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.

What types of projects do internship applied scientists in machine learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What are the key skills and qualifications needed to thrive as an internship applied scientist in machine learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Phoenix, AZ?

For Internship Applied Scientist Machine Learning jobs in Phoenix, AZ, the most frequently searched job titles are:

What job categories do people searching Internship Applied Scientist Machine Learning jobs in Phoenix, AZ look for?

The top searched job categories for Internship Applied Scientist Machine Learning jobs in Phoenix, AZ are:

Summer 2027 Intern - Machine Learning Engineering

Glendale, AZ • On-site


Workiva
Software Development • 1 - 5K employees

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 246 rated software companies

Great coworkers

People enjoy working here

Good employer


$40/hr

Other

Retirement

Posted 2 days ago

New


Job description

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the development, deployment, and monitoring of machine learning models. Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management and Analytics organization. This is an excellent opportunity to gain hands-on experience in the machine learning lifecycle.

What You'll Do

  • Participate in discovery, requirements gathering, and prototyping of new tools and libraries
  • Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer
  • Help integrate tools such as LlamaIndex and LlamaParse into existing workflows
  • Assist in building and deploying AI Agents to automate data processing and analysis tasks
  • Participate in code reviews
  • Implement and update tests (unit, integration)
  • Track tasks and complete status updates using internal tools
  • Work in an Agile development methodology alongside your teammates

What You'll Need

Minimum Qualifications

  • Currently pursuing a bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field of study
  • Possess solid programming skills
  • Basic experience with source control systems such as Git

Preferred Qualifications

  • Work effectively within a geographically distributed team
  • Demonstrate strong communication and organizational skills
  • Familiarity with the data science lifecycle and basic machine learning concepts
  • Experience with containerization tools such as Docker and Kubernetes
  • Knowledge of cloud platforms such as AWS
  • Proficiency with Python and/or Go
  • Familiarity with REST APIs

Travel Requirements & Working Conditions

  • Minimal travel
  • Reliable internet access for any period of time working remotely, not in a Workiva office

Location: This internship is primarily a remote opportunity. However, if you are located near one of our office hubs, you are welcome to work in a hybrid capacity and utilize our office spaces. Check out our article on Workplace Flexibility to learn more.

When can you expect to hear back?

We are committed to attending all career fairs and recruitment events before closing our positions. That means, this position might be open without updates for a few weeks to give us time to connect with all potential candidates before wrapping up the recruitment season. Check out our tentative timeline below to see when you can expect to hear from us!

Postings close: September 27, 2026

Engineering postings close: October 2, 2026

Interviews: Early to mid October

Offers: Late October

2027 Start Dates:

This position has opportunities to start in the Spring or Summer. Please see our start dates below and let us know your availability in your application.

  • Spring 2027 Internships: Monday, January 4, 2027 (15-20 hours per week max)
  • Summer 2027 Internships: Monday, May 17, 2027 (40/hours per week max)

How You’ll Be Rewarded

Salary range in the US: $40.00 - $40.00 401(k) participation and match

Paid sick leave

A unique opportunity to further your learning experience through additional internship seasons

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email earlycareer@workiva.com .

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.



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