Tensil

We turn machine learning models into custom hardware.

Lead FPGA Engineer at Tensil

$70k - $150k / 0.10% - 10.00%
Location
San Francisco, CA, USA / Remote
Job Type
Co-founder
Experience
3+ years
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Tom Alcorn
Tom Alcorn
Founder

About the role

We're developing new hardware accelerator architectures for running machine learning models. We have prototypes implemented on Xilinx FPGA's and we're looking for someone to expand this work into something that's ready for customers. This work will involve FPGA development work such as clock & resources optimization, floor-planning, debugging and host integration. It may also involve processor architecture design work such as micro-architectural optimizations and design for verification & test.

This is a job for a an experienced FPGA engineer who wants to get their hands dirty with a novel processing system and make significant contributions starting from day one. Depending on your priorities, this could be a simple full-time role or a co-founder position.

  • Clock optimization experience is a must-have
  • Key skills: Xilinx Vivado, Verilog, Tcl, Python
  • Familiarity with Chisel is a bonus (https://www.chisel-lang.org/)
  • Previous experience with machine learning accelerators will be helpful

Our website: https://www.tensil.ai

How we work: https://www.tensil.ai/about

Why you should join Tensil

Tensil automates machine learning hardware accelerator design. Our goal is to enable ML in every device. We've developed an algorithm that can design the best hardware accelerator for your machine learning model, unlocking 10x better performance per watt-dollar than GPUs and other accelerators. Our technology enables our customers to create unbeatable products with Tensil custom hardware at the core.

We're a very small, early stage team. Currently we are working with our first major partners to deliver a machine vision inference architecture for low-end FPGA platforms, with plans to expand into other platforms and applications. We're looking for hardware architects, especially those with FPGA expertise.