Senior FPGA Engineer

  • Permanent
  • New York
  • Location: New York, New York
  • Type: Permanent
  • Job #88908

My client are backed by top-tier investors, including the National Science Foundation and Felicis Ventures (early backers of Twitch, Shopify, and Canva). They are pioneering real-time, actionable insights from the radio spectrum using small, flexible sensors with powerful edge-based ML. Their product has significant defense applications, offering intuitive interfaces for easy understanding of the RF environment.
My client is building a highly skilled team to collaborate on some of the most challenging and exciting technical projects in the industry.

Teamwork and collaboration are highly valued, but there is also freedom to experiment, create independent projects, and act in the company’s best interests. My client emphasizes in-person collaboration and operates out of a spacious office in NYC, with room for new team members to join.

There is a strong belief in constant feedback and iteration, testing ideas to continuously improve. It's okay to make mistakes initially, as long as they contribute to finding the best solutions.

Responsibilities

  • Design, develop, and integrate FPGA platforms targeting Xilinx FPGAs.
  • Develop and maintain BSPs (Board Support Packages) for Petalinux integration.
  • Develop and verify custom IP blocks to implement or accelerate DSP and AI algorithms, interfacing with system software.
  • Participate in the architecture and design of Embedded Linux-based systems, efficiently distributing processing tasks among CPU, GPU, and custom accelerators to maximize throughput.

Requirements

  • Expertise in Xilinx Vivado & Vitis environments.
  • Experience in end to end full FPGA system design
  • Experience in developing FPGA systems from scratch, specifically targeting Zynq Ultrascale+.
  • Proficiency in SystemVerilog and/or VHDL.
  • Proficiency in C/C++.
  • Eligibility for US Security Clearance.

Nice-to-Haves

  • Experience using Vitis AI, Brevitas+FINN, and/or Vitis HLS toolchains.
  • Experience deploying ML models on embedded devices.
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