GenAI Performance Engineer, Modular

$167-286k

Canadian annual salary: $164,000.00 - $280,000.00 CAD. + Stock Options + Target Bonus

Python

Senior and Expert level

San Francisco Bay Area

Remote from Canada, US

More information about location

Fast, scalable Gen AI inference platform

Be an early applicant

Fast, scalable Gen AI inference platform

201-500 employees

B2BArtificial IntelligenceMachine Learning

Be an early applicant

$167-286k

Canadian annual salary: $164,000.00 - $280,000.00 CAD. + Stock Options + Target Bonus

Python

Senior and Expert level

San Francisco Bay Area

Remote from Canada, US

More information about location

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

5+ years of professional or postgraduate academic experience working on or researching performance analysis, tooling or benchmarking
Expertise in performance measurement (i.e. benchmarking), modeling, and analysis on real-world workloads
Extensive experience with Python
Creativity and curiosity for solving complex problems
Experience writing production-quality software
Strong written and verbal communication skills

What the job involves

ML developers today face significant friction in taking trained models into deployment
They work in a highly fragmented space, with incomplete and patchwork solutions that require significant performance tuning and non-generalizable/ model-specific enhancements
At Modular, we are building the next generation AI platform that will radically improve the way developers build and deploy AI models
A core part of this offering is providing a platform that allows customers to achieve state-of-the-art performance across use cases, model families, and hardware
As an GenAI Performance Engineer, you will join a small team of generalist engineers that optimize the performance of Modular’s MAX product in both breadth and depth
As part of deep dives on high-value models, you will collaborate with Kernel, Graph Compiler, and Cloud engineers to push Modular’s cutting-edge performance even further
Simultaneously, the performance team builds and applies performance analysis tooling to study and optimize the performance of MAX Engine and MAX Serve over a vast array of user configurations on a wide variety of CPU, GPU and Accelerator hardware
Measure, analyze, and identify opportunities to improve the performance of the MAX product under realistic and relevant usage patterns
Partner with the product and customer teams to understand the performance of the MAX product in both standard and cutting edge AI applications and design benchmarks to reflect them
Collaborate with the kernels and GenAI modeling team to bring up new model families
Collaborate with the kernels and runtime team to bring up and optimize new GPUs and accelerators
Collaborate with the cloud team to design and benchmark advanced serving features and new serving algorithms
Build statistical models and tools to operate on benchmarking & telemetry data and help develop key insights for performance, cloud costs, etc

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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