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Data Science Innovation Lead

1 week ago

Markham, Ontario, Canada Huawei Technologies Canada Co., Ltd. Full time

As a key member of the Computing Data Application Acceleration Lab at Huawei Technologies Canada Co., Ltd., you will have the opportunity to drive innovation in AI-powered big data platforms.

The lab focuses on creating a leading global data analytics platform using innovative programming technologies. This team specializes in full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers.

We aim to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness through cutting-edge technologies for AI-powered big data systems.

In this role, you will track emerging technical trends and developments for big data and AI systems in industry and academia. You will conduct in-depth analysis and identify directions for key cutting-edge technologies.

You will collaborate closely with stakeholders to comprehend business needs thoroughly. Translate these requirements into innovative technology solutions that align with organizational objectives.

Analyze and define key software requirements and features. Develop the proof-of-concept (PoC) AI-powered big data system infrastructure based on existing infrastructure and optimize its performance and performance per cost.

Integrate the PoC system into our existing product and deliver it to the production team.

Generate intellectual property such as patents and trade-secrets from research findings. Publish papers in peer-reviewed scientific journals/conferences.

Presents research findings at conferences and participates in research collaborations with external research institutes and universities.

About the ideal candidate:
  • MSc or PhD in Computer Science, Software Engineering, Computer Engineering, or related field.
  • 5+ years of professional software development experience with C++/Java, object-oriented design, and 2+ years of proven experience with platform/system level development.
  • Proficiency in at least one core big data system infrastructure, including Hadoop, Spark, Flink, Ray, Hive, HBase, MongoDB, and others.
  • Familiarity with recent machine learning, large language models, and generative AI models.
  • Knowledge of system/processor performance, CPU/GPU/NPU architectures, and compilers is an asset.
  • Familiarity with CICD tools like Git and Maven is an asset.
  • Able to work effectively individually and within a multi-zone and multi-site team.
  • Good communication, presentation, and collaboration skills.