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Machine Learning Engineer Intern Jobs in Arizona

Varsity Tutors

Machine Learning Tutor

Phoenix, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Mesa, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Chandler, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tucson, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Gilbert, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Intel

Density Fill Development Engineer Intern

Phoenix, AZ · On-site

$92.80K - $125.50K/yr

Join Intel as a Development Tools Software Engineering Graduate Intern and play a pivotal role in ... We encourage you to apply and be part of a collaborative environment that fosters learning, growth ...

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Machine Learning Engineer Intern information

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$23.8K

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

As of May 30, 2026, the average yearly pay for machine learning engineer intern in Arizona is $39,683.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.
More about Machine Learning Engineer Intern jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Arizona? The most popular types of Machine Learning Engineer jobs in Arizona are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Arizona? For Machine Learning Engineer Intern jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Arizona look for? The top searched job categories for Machine Learning Engineer Intern jobs in Arizona are:
What cities in Arizona are hiring for Machine Learning Engineer Intern jobs? Cities in Arizona with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Arizona as of May 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $39,683 per year, or $19.1 per hour.

Senior / Staff Machine Learning Infrastracture Engineer

Waabi

Phoenix, AZ • On-site, Remote

$157K - $234K/yr

Full-time

Posted 15 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor’s degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.