1

Staff Machine Learning Engineer Jobs in Arizona (NOW HIRING)

$40/hr

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 ...

$40/hr

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 ...

$40/hr

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 ...

$40/hr

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 ...

$40/hr

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 ...

$40/hr

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 ...

Showing results 41-60

Staff Machine Learning Engineer information

See Arizona salary details

$21.4K

$92.6K

$179.4K

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

As of Sep 5, 2026, the average yearly pay for staff machine learning engineer in Arizona is $92,564.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,300.00 and $116,500.00 per year, depending on experience, location, and employer.

What is a staff machine learning engineer?

A Staff Machine Learning Engineer is a senior-level technical role responsible for designing, deploying, and optimizing machine learning models at scale. They provide technical leadership, mentor other engineers, and drive best practices in ML system architecture. This role often involves collaborating with cross-functional teams, improving model performance, and ensuring the reliability of machine learning solutions in production. Staff ML Engineers typically have deep expertise in algorithms, data infrastructure, and engineering processes. Their work focuses on solving complex problems and influencing the broader ML strategy within an organization.

What are the typical collaboration and leadership responsibilities for a staff machine learning engineer?

As a Staff Machine Learning Engineer, you often serve as a technical leader, partnering with cross-functional teams including data scientists, product managers, and software engineers to develop and deploy machine learning solutions. You will mentor junior engineers, conduct code reviews, and help establish best practices for model development and deployment. In addition to hands-on technical work, you may be responsible for evaluating new tools, contributing to the broader ML strategy, and facilitating knowledge sharing sessions. This collaborative and leadership-focused approach helps ensure consistency, quality, and innovation across machine learning projects.

What are the key skills and qualifications needed to thrive in the staff machine learning engineer position, and why are they important?

To thrive as a Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, data analysis, and typically a strong academic background in computer science or related fields. Experience with Python, TensorFlow, PyTorch, cloud platforms, and a track record of delivering production-level ML systems are crucial, as are advanced degrees or relevant certifications. Strong leadership, communication, and mentoring skills help you effectively guide teams and collaborate across departments. These competencies are essential for designing robust ML solutions, leading technical initiatives, and ensuring successful project delivery in complex organizational environments.

Do staff machine learning engineers get paid well?

Staff machine learning engineers typically earn high salaries due to their advanced skills, experience, and expertise in developing complex models and deploying AI solutions. Compensation often includes base salary, bonuses, and stock options, reflecting their seniority and impact within organizations.

What are the most commonly searched types of Staff Machine Learning Engineer jobs in Arizona?

The most popular types of Staff Machine Learning Engineer jobs in Arizona are:

Infographic showing various Staff Machine Learning Engineer job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, 1% Temporary, and 4% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $92,564 per year, or $44.5 per hour.

Summer 2027 Intern - Machine Learning Engineering

Workiva

Yuma, AZ • On-site, Remote

$40/hr

Full-time, Temporary, Internship

Retirement

Posted 5 days ago


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 247 rated software companies


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.


What Workiva employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom