About Partcl

Design a chip in minutes

Tech description:

Job description:

Partcl is the vibe coding platform for chip designers. I was told to make this job description “sound cool and not corporate” so I had ChatGPT translate it into gen alpha: EDIT: We had an overwhelming number of applicants, so we’re having everyone do a short take home challenge and we’ll interview the people who do well on this: https://github.com/partcleda/intern_challenge ### **About Partcl** We’re cooking the next wave of chip‑design automation—built for speed, scale, and builder productivity. We believe AI should level up hardware engineering, and the first W is smarter optimization tools. If you want to tackle massive‑scale problems in physical AI, Partcl is the move. ### **What you will do:** * **Cook + train custom models** to go after **NP‑complete** optimization problems (smart heuristics that actually ship, fr) * **Spin high‑perf CUDA kernels** for **training + inference** and make them _zoom_ * **Speedrun parsers** that chew through massive files without choking * **Build ultra‑lean, cache‑friendly data structures** — minimal mem, max throughput * **Hook up an LLM interface** to those structures so users can literally talk to their design ### **What you bring:** * **Python + PyTorch skills** from classes or projects; you’ve trained & evaluated custom models (not just “wrapped a GPT,” fr) * **Systems intuition**: you grok memory hierarchies, latency vs. throughput trade‑offs, & why cache misses make everyone sad * **Some CUDA exposure** _or_ you’re dangerously motivated to pick it up fast—kernels don’t scare you * **Range**: you can bounce between model design, low‑level perf work, and scalable system plumbing (think **N → 10M+**) * **Tooling chops**: you’ve at least dabbled in GPU profiling/perf analysis and you’re down to go deeper ### **Bonus XP (nice to have)** * Any exposure to **EDA / chip design** flows * **Reinforcement Learning** beyond toy notebooks * Research or serious projects in **compilers / programming languages / databases** * **Publications** in respected venues (conference/journal/tech reports) * **Physics‑driven ML** or numerics that make simulators blush ### **Why this rocks** * Work on problems where milliseconds matter and terabytes aren’t “big,” they’re Tuesday. * Ship code that touches real silicon workflows. * Learn from builders who live at the ML × systems × hardware edge. **Pull up with your resume/portfolio/GitHub. Let’s build.**

Skills:

Torch/PyTorch, Rust, GPU Programming, Machine Learning, CUDA

Partcl remote jobs

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Summer 2026 ML Systems Intern

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