Kernel Engineer (Internship and Full-time)
Tilde Research
Apply to this jobTilde Research is a moonshot AI lab advancing mechanistic interpretability, new architectures, and pretraining science. We build foundational understanding of models to advance the frontier of intelligence.
About the role:
As a Kernel Engineer at Tilde, you'll design, implement, and optimize high-performance GPU kernels that are critical to scaling our training and inference workloads. Your work will enable faster iteration cycles, higher throughput, and lower latency. You'll work closely with ML researchers and engineers to co-design models and infrastructure that are deeply performance-aware, and help push the limits of what current hardware can support.
What you might work on:
Design, develop, and tune custom GPU kernels for core model operations
Work with ML engineers to prototype and scale novel model architectures
Contribute to system-wide efforts to improve efficiency and throughput, beyond just kernel-level optimizations
You're a good fit if you:
Have experience in deep learning or related research areas
Have demonstrated exceptional capability in working on ML kernels. This can include:
Strong open source contributions
Thoughtful technical blog posts/work logs
Previous experience working on hardware-aligned algorithms
Deep familiarity with PyTorch, Triton/TK/TileLang (>1 of), basic familiarity with CUDA, and knowledge of GPU architecture.
Communicate clearly and effectively, both verbally and in writing
Strong algorithmic thinker
Are able to learn quickly
Summary
Design, develop, and optimize GPU kernels for ML workloads in a research setting.
Job title
Kernel Engineer (Internship and Full-time)
Experience level
Industry
technology
Location requirements
San Francisco, on-site work required.
Salary
Not specified
Management role
No
Required skills
Preferred skills
Specializations
Structured locations inferred from the posting.
San Francisco, CA, USA