Quality Engineering Intern

About Modular At Modular, we're on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up.

Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment.

By rethinking the complexities of AI systems, we're empowering everyone to unlock AI's full potential and tackle some of the world's most pressing challenges.

If you're passionate about shaping the future of AI and creating tools that make a real difference in people's lives, we want you on our team.

You can read about our culture and careers to understand how we work and what we value.

What You Will Work On: As an intern on the Quality Engineering team, you will help improve the accuracy, reliability, and evaluation strategy of Modular's AI/ML products.

You will work across model, inference, and platform teams to define what "good" looks like, build the frameworks to measure it, and implement strategies to prevent regressions.

Typical projects may include: * Building and extending accuracy and evaluation frameworks (golden test suites, regression dashboards, CI gating) for core MAX workflows.

* Defining quality strategies for new features, including metric selection, acceptance criteria, and release readiness checks.

* Creating reproducible test harnesses that exercise real-world workloads across models, prompts, and hardware.

* Investigating accuracy issues, triaging failures, and partnering with engineering teams to drive fixes.

* Improving the developer experience around quality by making tests faster, more informative, and easier to run locally.

LOCATION: Candidates based in the United States are welcome to apply.

To support growth and collaboration, all interns will work in a hybrid capacity at our Los Altos, CA office (minimum 2 days per week on-site) with relocation assistance provided for out-of-state candidates.

What You Will Learn: * How to design accuracy metrics and evaluation methodologies for modern AI systems.

* How to build scalable quality infrastructure that integrates with CI/CD and release processes.

* How to collaborate across teams to translate product goals into measurable quality targets.

* Mentorship from engineers working on AI infrastructure and quality.

About You: * Currently pursuing a Bachelor's, Master's, or PhD degree with graduation expected by Spring 2027 at the latest.

* Experience with Python.

* Familiarity with software testing practices (unit/integration testing, CI) and a desire to apply them to AI/ML systems.

* Interest in evaluation, measurement, and debugging (for example: metrics, test design, failure analysis, reproducibility). * You have strong verbal and written communication skills, and ability to articulate your thoughts clearly and professionally.

* You are detail-oriented and able to adapt to a fast-paced environment.

* You have a strong demonstrated interest in working with people, and an eagerness to learn about the AI/ML industry.

* You can demonstrate creativity and curiosity for solving complex problems, a team-oriented attitude that enables you to work well with others, and alignment with our culture.

What Modular brings to the table: * Amazing Team.

We are a progressive and agile team with some of the industry's best engineering and product leaders.

* Competitive Compensation.

We offer very strong compensation packages, including stock options.

We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.

* Team Building Events.

We organize regular team onsites and local meetups in Los Altos, CA.

Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.

The estimated base salary range for this role is $100,000.00 - $130,000.00 USD.

The salary range for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands.

This range may be modified in the future.

For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.