Inference Intern
Etched · San Jose
CHECKED 8H AGO
Infrastructureonsiteintern
At a glance
Highlights
- Port state-of-the-art models to next-gen AI accelerator architecture.
- Help scale runtime with multi-node inference and robust error handling.
- Co-design hardware instructions and model ops for max performance.
What they offer
- 12-week paid internship
- Generous housing support for relocation
- Daily lunch and dinner in office
- Direct mentorship from industry leaders
Ideal candidate
A performance-obsessed CS student excited by hardware-software co-design and pushing frontier inference to its limits on novel accelerators.
Requirements
- Pursuing Bachelor's, Master's, or PhD in CS, computer engineering, applied math, or related field
- Proficiency in Python and C++
- Understanding of performance-sensitive distributed systems like Linux internals, GPUs, compilers, or high-speed interconnects
- Experience porting applications to non-standard accelerator hardware
- Deep knowledge of transformer architectures and inference serving stacks like vLLM or SGLang
- remote policy
- Fully in-person
Lab profile
About Etched
Building specialized AI chips and systems for frontier inference with best-in-class throughput and latency.
What they build
- Sohu AI inference chip
- AI racks and hardware systems
- Inference software stack
Known for
- Full-stack co-design of chips, racks, software and manufacturing
- Best-in-class throughput and latency for prefill and decode
- Inference-optimized architecture
Key facts
- Backed by hundreds of millions from top-tier investors