Senior Researcher – Hardware Acceleration for Big Data

Huawei Canada; Markham; On-site; CAD 80,000 - 100,000; Full time

Job summary

An established industry player is seeking a Senior Researcher to join their innovative Computing Data Application Acceleration Lab. This role focuses on advancing data analytics platforms through cutting-edge software-hardware co-design technologies. The ideal candidate will leverage their extensive research experience to enhance algorithm performance and contribute to next-generation chip designs. If you are passionate about hardware design and eager to make a significant impact in the fields of big data and AI, this opportunity is perfect for you. Join a dynamic team that values collaboration and innovation, and help shape the future of technology.

Qualifications

• Minimum 5 years of experience in hardware modeling and design.
• Hands-on experience in ASIC/FPGA hardware design and EDA toolflow.

Responsibilities

• Conduct research on emerging hardware designs and software/hardware co-design.
• Collaborate with big data teams to optimize data-intensive applications.

Skills

C/C++

Verilog

FPGA design

ASIC design

Research skills

Communication skills

Education

MSc in Computer Engineering

PhD in Computer Engineering

MSc in Electrical Engineering

PhD in Electrical Engineering

MSc in Computer Science

PhD in Computer Science

Tools

gem5

Sniper

GPGPU-Sim

Multi2Sim

Job description

Huawei Canada has an immediate permanent opening for a Senior Researcher.

About the team:

The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications.

One of the goals of this lab is to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.

About the job:

• Track the emerging hardware designs in both industry and academia, conduct in-depth insight and survey analysis, and identify the direction of key cutting-edge software/hardware co-design technologies.
• Cooperate with our big data team to identify key performance bottlenecks in big data workloads, define key software/hardware co-design features of our next-generation chips, design and implement proof-of-concept (PoC) domain-specific accelerators tailored for data-intensive applications.
• Publish research papers, and/or file patents, and influence stakeholders by providing insights and guidance on technical planning and investigation direction for Huawei's big data solutions, especially our next-generation chips. Ensure alignment with organizational objectives.
• Present research findings at conferences and participate in research collaborations with external research institutes and universities.

About the ideal candidate:

• Holds a MSc or PhD in Computer Engineering, Electrical Engineering, or Computer Science, or reflecting a solid academic foundation for the role.
• Accumulates a minimum of 5 years of research/engineering experience (including research/engineering experience during PhD/MSc study), showcasing excellence in hardware modeling and design.
• Demonstrates hands-on experience in designing, developing, synthesizing, and/or verifying ASIC or FPGA hardware designs.
• Demonstrates hands-on experience in electronic design automation toolflow for ASIC/FPGA hardware designs, and/or computer architecture simulators (e.g., gem5, Sniper, GPGPU-Sim, Multi2Sim, etc.).
• Exhibits expertise in coding language such as C/C++, and a hardware language like Verilog/ VHDL/SystemVerilog/Chisel or similar low-level languages.
• Familiarity with big data/database or AI research and development is an asset.
• Ability to work effectively both individually and within a multi-zone and multi-site team, contributing seamlessly to collaborative efforts.
• Good communication, presentation, and collaboration skills. Proficient in leveraging resources from both industry and academia.