Technology Ecosystem & Academic Relations Lead
huaweicanada · Markham
Job description
About the role
Huawei Canada is seeking a Technology Ecosystem & Academic Relations Lead on a 12‑month contract to strengthen its external technology network and foster collaborations with universities, research labs, startups and industry groups. The role bridges academic research and Huawei’s strategic technology planning, helping the institute stay at the forefront of AI, computing and open‑source ecosystems.
Key responsibilities
- Build and maintain relationships with universities, research institutes, enterprise labs, open‑source communities, startups and industry organizations.
- Identify and profile key professors, researchers, architects, engineers, founders and product leaders.
- Create expert, institution and technology landscape maps and develop collaboration pipelines.
- Attend major AI, systems, semiconductor and open‑source conferences to capture industry trends.
- Design and organize technical workshops, seminars, closed‑door roundtables and expert visits.
- Translate workshop outcomes into expert relationships, technical insights and potential collaborations.
- Convert fragmented external information into actionable internal intelligence.
- Identify and advance collaboration opportunities aligned with the institute’s strategic research directions.
Required profile
- Solid understanding of at least two of the following areas: AI (foundation models, multimodal AI, agentic systems), computing architecture (AI chips, GPUs, heterogeneous computing), operating systems, databases, compilers, distributed systems, developer tools, model serving, inference engines, cloud/edge computing, AI platforms, emerging devices (XR, robotics), open‑source communities.
- Professional communication skills with professors, academic researchers, enterprise scientists, technical investors and venture partners.
- Proven ability to independently or jointly organize high‑quality technical events such as workshops, seminars, roundtables and academic exchanges.
- Capability to summarize expert views, write technology trend reports, and produce expert and institution maps.
- Experience providing structured inputs for executives, research leaders and technical teams.
- Experience in universities, research institutes, corporate research labs, technology strategy or developer ecosystem teams is an asset.
- Experience organizing academic conferences, technical workshops or industry forums is an asset.
- Master’s or PhD‑level research experience.
Required skills
- Artificial Intelligence (AI) and foundation models
- Multimodal AI and agentic systems
- Computing architecture, AI chips, GPUs, heterogeneous computing
- Operating systems, databases, compilers, distributed systems
- Developer tools and software engineering infrastructure
- Model serving, inference engines, cloud computing, edge computing, AI platforms
- Emerging devices such as XR, robotics, AI PCs, AI phones
- Open‑source communities and developer ecosystems
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Published 18 hours ago
Expires 1 month from now
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huaweicanada
Markham