Kernel Engineer (Internship and Full-time) at Tilde Research (San Francisco, CA)
Tilde Research· San Francisco, CA·
Role details
Job description
Tilde 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
Why work at Tilde Research
- Cutting‑edge research – work on the hardest problems in AI interpretability and architecture design.
- Small lab culture (≈6 people) – high ownership, rapid iteration, direct impact on flagship projects.
- Moonshot mentality – not product‑driven, but driven by the pursuit of understanding; ideal for researchers who value fundamental science.
- Strong network effects – team members come from top institutions and labs; alumni go on to places like Nous Research, Forgepoint Capital, and Stanford.
- Career development – offers both internships and full‑time roles; the interview process includes a graph theory problem that showcases the lab’s intellectual rigor.
- Location: San Francisco (headquarters) – likely in‑person or hybrid given the small team size; specific remote policy is not publicly stated.