Edge AI FPGA Architect for Spatial Vision & SLAM

O-HIVE.AI; Windsor; On-site; CAD 85,000 - 120,000; Full time

Benefits offered by this job

Direct contribution to ASIC technology

Hands-on hardware experience

Exposure to FPGA prototyping to ASIC

International engineering teamwork

Job summary

O-HIVE is seeking a talented FPGA Engineer to join the engineering team and contribute to hardware-accelerated spatial vision and edge AI systems.

The role involves designing, implementing, and optimizing FPGA-based architectures for real-time computer vision, SLAM, object detection, and AI inference, collaborating with AI researchers, software engineers, and ASIC designers to move algorithms into production hardware.

Qualifications

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related.
• Practical experience developing FPGA designs with Verilog, SystemVerilog, or VHDL.
• Familiarity with AMD/Xilinx or Intel/Altera FPGA development environments.
• Experience with FPGA synthesis, implementation, timing closure, and debugging.
• Understanding of digital logic, pipelining, parallel processing, and memory architecture.
• Proficiency in C/C++ or Python for testing and hardware integration.
• Knowledge of embedded systems and hardware/software interfaces.

Responsibilities

• Design and implement FPGA-based accelerators for real-time vision workloads.
• Develop hardware processing pipelines for image processing and AI workloads.
• Optimize designs for latency, throughput, power, and resources.
• Interface with SLAM and computer vision frameworks and ASIC teams.
• Document hardware modules, interfaces, and performance characteristics.

Skills

FPGA design

Verilog/SystemVerilog

VHDL

C/C++

Python

Embedded systems

Digital logic design

Debugging

Education

Bachelor's or Master's degree in Electrical Engineering

Tools

AMD Xilinx Vivado

Vitis

Intel/Altera tools

HDL simulators

Job description

O-HIVE is seeking a talented FPGA Engineer to join the engineering team and contribute to hardware-accelerated spatial vision and edge AI systems.

The role involves designing, implementing, and optimizing FPGA-based architectures for real-time computer vision, SLAM, object detection, and AI inference, collaborating with AI researchers, software engineers, and ASIC designers to move algorithms into production hardware.