Fpga design engineer Jobs

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Computer Vision Engineer, FPGA

LUCID Vision Labs -
Burnaby, BC

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Job details

Qualifications

MATLAB
Doctoral degree
Computer Science
Signal processing
FPGA
Engineering
Firmware
Master's degree
Verilog
Algorithm design
Computer Engineering
Electrical Engineering
Communication skills
Sensors
Python
Debugging

Full job description

Job Title: Computer Vision Engineer, FPGA – Burnaby BC

Reports To: Engineering Manager, FPGA

Job Purpose
The Computer Vision Engineer, FPGA Implementation will develop and implement advanced image processing algorithms for LUCID’s industrial machine vision cameras. This role focuses on designing, modeling, validating, and optimizing computer vision and image signal processing algorithms, then translating selected algorithms into efficient FPGA-based implementations for real-time, low-latency camera operation. The ideal candidate has strong computer vision and image processing knowledge, practical software prototyping experience in Python, MATLAB, or similar tools, and some familiarity with hardware design constraints. Direct FPGA experience is highly valuable, but candidates with strong algorithm development skills and a willingness to learn FPGA implementation may also be considered.This role will support development across standard area-scan image signal processing, line-scan image processing, and 3D/time-of-flight imaging pipelines.

Duties and Responsibilities

Research, design, and prototype image processing and computer vision algorithms for industrial camera products.
Develop algorithm models, simulations, and test environments using Python, MATLAB, or similar tools.
Evaluate algorithm performance using image quality metrics, simulation data, test images, and real camera data.
Refine algorithms based on image quality, performance, latency, robustness, and implementation feasibility.
Develop and support image signal processing algorithms for area-scan, line-scan, and time-of flight camera pipelines.
Model data flows and makes architectural decisions based on product requirements, schedule, device limitations, bandwidth, latency, and system-level constraints.
Convert selected software-based algorithms into efficient FPGA implementations using VHDL.
Optimize FPGA implementations for latency, resource utilization, timing performance, memory bandwidth, and target camera constraints.
Simulate and validate FPGA-based image processing blocks.
Contribute to integration of processing blocks into larger FPGA and camera system architectures.
Document algorithm behavior, architecture decisions, design requirements, interfaces, implemen tation details, and verification results.
Stay informed on relevant developments in image processing, computer vision, FPGA implemen tation methods, camera ISP design, and time-of-flight imaging.

Qualifications/Education/Skills

Master’s or PhD (preferred) degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field.
Experience developing camera ISP pipelines for area-scan or line-scan image sensors.
Experience with time-of-flight imaging, depth processing, 3D imaging, or related calibration and correction algorithms.
Experience with stereo vision, image warping, compression, HDR processing, or camera calibration.
Experience with real-time, low-latency image processing systems.
Experience converting floating-point software models into fixed-point or hardware-efficient implementations.
Experience with high-level modeling, hardware/software co-design, or top-down algorithm-to-hardware workflows.
Experience implementing production FPGA designs using VHDL or Verilog.
Experience with Xilinx/AMD or Intel/Altera FPGA development tools.
Experience with FPGA simulation, timing closure, resource optimization, and in-system debugging.
Knowledge of sensor interfaces, camera architectures, or embedded systems.
Understanding of CPU, GPU, and FPGA architecture trade-offs.
Experience contributing to products shipped in volume.
Experience with image signal processing algorithms such as demosaicing, color correction, auto exposure, auto white balance, tone mapping, sharpening, denoising, geometric correction, or image enhancement.
Experience developing, modeling, and evaluating algorithms in Python, MATLAB, or similar environments.
Ability to evaluate algorithm performance using test data, image quality analysis, simulation results, and real-world imaging conditions.
Ability to translate algorithmic concepts into practical implementations with real-world performance, memory, latency, and compute constraints.
Familiarity with digital hardware concepts such as fixed-point arithmetic, pipelining, streaming data paths, memory interfaces, and resource-limited design.
Strong debugging, analysis, documentation, and communication skills.
Ability to work collaboratively across hardware, firmware, software, and product development teams.

Apply Now

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