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Inference Intern

Etched· Architecture
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San JoseInternPosted 3mo ago

About the role

Internship focused on designing and optimizing next-generation AI accelerators for inference workloads, with emphasis on performance modeling, architecture exploration, and software-hardware co-design.

Responsibilities

  • Support porting state-of-the-art models to our architecture. Help build programming abstractions and testing capabilities to rapidly iterate on model porting.
  • Assist in building, enhancing, and scaling our runtime, including multi-node inference, intra-node execution, state management, and robust error handling.
  • Contribute to optimizing routing and communication layers using our collectives.
  • Utilize performance profiling and debugging tools to identify bottlenecks and correctness issues.
  • Develop and leverage a deep understanding of our architecture to co-design both HW instructions and model architecture operations to maximize model performance
  • Implement high-performance software components for the Model Toolkit

Qualifications

  • Progress towards a Bachelor’s, Master’s, or PhD degree in computer science, computer engineering, applied mathematics, or a related field
  • Proficiency in Python, C++
  • Understanding of performance-sensitive or complex distributed software systems, e.g. Linux internals, accelerator architectures (e.g. GPUs, TPUs), Compilers, or high-speed interconnects (e.g. NVLink, InfiniBand).
  • Ported applications to non-standard accelerator hardware or hardware platforms.
  • Deep knowledge of transformer model architectures and/or inference serving stacks (e.g. vLLM, SGLang, etc.)

Skills

Required:PythonC++

Benefits

  • 12-week paid internship
  • Generous housing support for those relocating
  • Daily lunch and dinner in our office
  • Direct mentorship from industry leaders and world-class engineers
  • Opportunity to work on one of the most important problems of our time
Last updated Oct 22, 2026. Interested? Apply on the company site.
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About Etched

Etched is building frontier inference clusters: co-designs chips, racks, software and manufacturing to push the pareto frontier for AI hardware.

frontier inference clustersAI hardwarechipsrackssoftwaremanufacturingparto frontier
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