Ludwig Computing
FPGA Intern – Custom Compute Hardware
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Apply to FPGA Intern – Custom Compute Hardware at Ludwig ComputingJob details
- Work type
- Remote
- Visa
- Sponsorship available
- Posted
- 1 week ago
- Apply on
- jobs.gusto.com
About this role
Ludwig Computing is focused on solving the energy efficiency problem of intelligent compute through innovative hardware and software platforms. They are seeking a Hardware Engineer intern to assist in FPGA-based prototyping and hardware bring-up, working directly with the founding team on core logics and processing algorithms.
What you'll do:
- Translate architectural concepts into FPGA prototypes
- Design and simulate custom processing modules using Verilog, VHDL, or high-level synthesis (HLS)
- Implement and validate processing components on FPGA platform using industry-standard tools (e.g., Vivado, Quartus, or OpenCL-based flows)
- Benchmark performance and optimize tradeoffs in latency, area, throughput, and memory bandwidth
- Build testbenches, run timing/area analysis, and assist with system integration
- Collaborate with the team to define hardware/software boundaries, and support bring-up of real demos
What they're looking for:
- Experience with FPGA development, RTL or HLS-based design in Verilog/SystemVerilog, VHDL, or C++
- Familiarity with FPGA development tools (Vivado, Quartus, or equivalent)
- Strong grasp of digital logic fundamentals, including pipelining and timing closure
- Experience with memory mapping and hierarchy on FPGA
- Strong skills in simulation, debugging, and synthesis workflows
- Currently pursuing a degree in engineering (preferably Electrical Engineering, Computer Science)
- Experience with OpenCL or HLS-based design targeting FPGA
- Prior Experience with FPGA development boards
- Familiarity with hardware/software co-design and system-level integration
- Course work or project experience in digital design, computer architecture, or embedded systems
- Understanding of memory system tradeoffs
- Exposure to numerical computing, or custom arithmetic units
Benefits:
- Opportunity to work on next generation AI compute architectures
- Hands-on experience building novel, high-speed, energy-efficient compute accelerators on FPGAs
- Opportunity to build skills that bridge into ASIC flows, including RTL quality, test benching, and synthesis-readiness
- Mentorship from a team with expertise in hardware-software co-design, digital architecture, and early-stage prototyping
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