FPGA Engineer — Custom Compute Hardware

Job Title

FPGA Engineer — Custom Compute Hardware

Role Summary

Hands-on internship on FPGA architecture, implementation, verification, and testing for custom compute accelerators. Work with the founding team to implement and validate core logic, processing algorithms, and subsystem integration for energy-efficient AI compute platforms.

This is an R&D-focused role combining prototype development, benchmarking, and system-level integration across FPGA and early ASIC flows.

Experience Level

Internship — Entry-level. Suitable for students or early-career engineers with FPGA/RTL experience seeking practical, project-based work.

Responsibilities

Key technical responsibilities for the role:

• Translate architectural concepts into FPGA prototypes and hardware implementations.
• Design and simulate custom processing modules using Verilog, VHDL, SystemVerilog, or HLS.
• Implement and validate components on FPGA platforms using Vivado, Quartus, or equivalent flows.
• Develop testbenches, run timing and area analysis, and support timing closure.
• Benchmark performance and optimize latency, area, throughput, and memory bandwidth tradeoffs.
• Generate and execute FPGA verification test plans and verification matrices.
• Collaborate with system architects, FPGA design engineers, and embedded software engineers for system integration.

Requirements

Must-have technical skills and practical experience:

• Experience with FPGA development and RTL or HLS-based design in Verilog/SystemVerilog, VHDL, or C.
• Familiarity with FPGA development tools (Vivado, Quartus, or equivalent).
• Solid electronic circuit design and electronic systems background.
• Strong understanding of digital logic fundamentals, including pipelining and timing closure.
• Experience with digital system partitioning and implementing advanced functions on FPGAs.
• Experience with memory mapping and hierarchy on FPGA platforms.
• Strong skills in simulation, debugging, synthesis workflows, and practical verification.
• Ability to work in a fast-paced R&D environment on prototype and proof-of-concept projects.

Nice-to-have:

• Experience with OpenCL or HLS-based FPGA flows.
• Hardware/software co-design and system-level integration experience.
• Project experience in digital design, computer architecture, or embedded systems.
• Exposure to numerical computing, AI workloads, or custom arithmetic units.
• Familiarity with ASIC concepts (synthesis, floorplanning, RTL-to-GDS) and high-speed interfaces.
• Familiarity with analog or mixed-signal concepts.

Education Requirements

B.S. degree or higher in engineering (preferably Electrical Engineering or Computer Science).

About the Company

Company: Ludwig Computing

Ludwig Computing develops energy-efficient AI compute hardware and software using a co-designed approach to deliver high-performance, low-power accelerators. The company focuses on custom compute platforms, FPGA prototyping, and ASIC-relevant flows for AI and high-performance workloads.