
The next-generation AI developer platform unifying the development and deployment of AI for the world.

The next-generation AI developer platform unifying the development and deployment of AI for the world.
Founders: Chris Lattner (Co‑Founder & CEO) and Tim Davis (Co‑Founder & President); founded 2022
What they build: A unified AI compute layer and modular infrastructure for high‑performance, GPU‑portable model development and serving
Flagship products: MAX (scalable AI deployment/serving) and Mojo (high‑performance, Python‑compatible programming language)
Funding & valuation: $380M total raised across three rounds; $250M round announced Sept 24, 2025; reported valuation $1.6B
Notable investors: Investors include GV (Google Ventures), General Catalyst, Greylock, SV Angel, The Factory, DFJ Growth, and US Innovative Technology
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AI infrastructure: compute portability, inference/serving, and developer tooling for high‑performance AI workloads.
2022
Software Development
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TechCrunch reported a $30M seed round with participation from Greylock, The Factory, and SV Angel.
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Round reported as led by General Catalyst with participation from GV, SV Angel, Greylock, and The Factory; brought reported total to ~$130M at the time.
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Modular announced a $250M financing, bringing reported total capital raised to $380M across three rounds and reporting a $1.6B valuation; DFJ Growth and existing investors participated.
“Backed by established venture firms and growth investors, including GV (Google Ventures), General Catalyst, Greylock, SV Angel, The Factory, DFJ Growth, and US Innovative Technology.”
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 AI Kernel Engineering Intern, you will work at the intersection of AI inference models and cutting edge, high-perform GPU kernels. You will help design, optimize, and benchmark low-level kernels that power modern AI workloads, with a focus on GPUs and emerging accelerators. Projects may include optimizing matrix operations, attention primitives, or custom operators; analyzing memory layouts and data movement; and collaborating with others to translate models into efficient, production-ready implementations.
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 You will gain hands-on experience with the internals of AI frameworks and hardware-aware optimization. This includes understanding how deep learning operators map to GPU architectures, writing and tuning GPU kernels, and using profiling tools to identify performance bottlenecks. You’ll also learn best practices for performance-critical code, numerical correctness, and collaborating across teams to deliver impactful improvements.
What You Bring To The Table
What Modular Brings To The Table
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 hourly range for this role is $47.00 - $65.00 USD .
The hourly rate 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.