Quality Engineering Intern, Modular

$100-130k

+ Stock options

Python

Spring

San Francisco Bay Area

More information about location

2+ days a week in office (Los Altos, CA)

Fast, scalable Gen AI inference platform

Job no longer available

Fast, scalable Gen AI inference platform

201-500 employees

B2BArtificial IntelligenceMachine Learning

Job no longer available

$100-130k

+ Stock options

Python

Spring

San Francisco Bay Area

More information about location

2+ days a week in office (Los Altos, CA)

201-500 employees

B2BArtificial IntelligenceMachine Learning

Company mission

To have real, positive impact in the world by reinventing the way AI technology is developed and deployed into production with a next-generation developer platform.

Job

Company

Role

Who you are

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 the job involves

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
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

Our take

AI development is booming, but the tools behind it? Not so much. Developers are often stuck dealing with messy, disconnected systems that slow everything down and bump up costs.

To address this, Modular has developed a unified AI platform that streamlines the development process. It's AI Engine enhances the performance of models on CPUs and GPUs, supporting popular frameworks like TensorFlow and PyTorch. And on top of that, it's built Mojo, a programming language that's as easy as Python but much faster (35,000 times faster).

In 2023, the company raised an impressive $100M to power its mission. It's been using this funding to grow its team, support more hardware, and push Mojo even further. With the hopes of making AI development faster, smoother, and a whole lot more fun for everyone.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 3 rounds)

Sep 2025

$250m

LATE VC

Aug 2023

$100m

LATE VC

Total funding: $380m

Company benefits

A variety of fantastic health benefits (health, dental, vision insurance; life insurance etc) are available
A 401k plan with up to 5% match
Free tax advice on Carta
Generous work-from-home stipend of $1500 to help you improve your home office
Unlimited paid time off and flexible work hours

Leadership

Chris Lattner

(Co-Founder & CEO)

Founder, Architect, Engineer and BDFL for the LLVM Organization. Former President of Engineering and Product at SiFive, as well as working in various roles at Google, Tesla, and Apple.

Tim Davis

(Co-Founder & President)

Worked at Google for 5 years, ultimately as Group Product Lead for Google ML. Previously founded Fluc Inc, where they developed the entire ML powered delivery system with their co-founder, and mapping software system CrowdSend.

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