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Research Scientist – Efficient and Controllable Generative Models

Job in Zürich, 8081, Zurich, Kanton Zürich, Switzerland
Listing for: Huawei
Full Time position
Listed on 2026-09-22
Job specializations:
  • IT/Tech
    AI Business & Operations, Data Scientist
  • Research/Development
    AI Business & Operations, Data Scientist
Salary/Wage Range or Industry Benchmark: 130000 - 180000 CHF Yearly CHF 130000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Zürich

Huawei envisions a world where technology connects people, empowers industries, and unlocks human potential.

Guided by its mission to enrich lives through communication and intelligent innovation, Huawei stands at the forefront of global digital transformation. As a leader in Information and Communications Technology (ICT), the company pioneers breakthroughs in artificial intelligence, cloud computing, and smart devices - building the intelligent foundation of a fully connected world.

Through its Carrier, Enterprise, and Consumer business groups, Huawei delivers resilient digital infrastructure, advanced cloud and AI platforms, and transformative devices that enable progress at every level. Supporting 45 of the world’s top 50 telecom operators and serving one-third of the global population across more than 170 countries, Huawei is shaping a future where connectivity becomes a powerful catalyst for opportunity and sustainable growth.

About

The Role

The Computer Vision and Machine Learning Lab at Huawei Research Center in Zurich is looking for a Research Scientist to push the frontier of generative modeling and bring it to hundreds of millions of devices. You will conduct cutting-edge research on generative models for images, video, and 3D/4D content, with two goals at the center of your work: making these models efficient enough to run on-device, and making them predictable and controllable enough to be trusted in a product.

Generative models in consumer products must not only be fast; they must be reliable. Distorted faces, hallucinated or garbled text, altered identities, inconsistent geometry, and temporal flicker are unacceptable in a flagship camera or editing feature. You will develop methods that keep generation faithful to the input and to user intent, while running under real memory, latency, and power constraints.

The research is primarily applied to camera and imaging, image and video processing and understanding, and graphics: generative enhancement and editing of photos and videos, 3D-aware capture and reconstruction, dynamic scene understanding, and real-time rendering and content creation. Your work will directly shape next-generation Huawei consumer products, including flagship smartphones, laptops, tablets, and autonomous vehicles.

This is a role for someone who wants to publish at top venues and see their research ship.

What you will do
  • Conduct original research on efficient generative models, including diffusion and flow-based models, few-step and one-step generation, distillation, quantization, and architectures co-designed with mobile and automotive hardware.
  • Develop methods for controllable and reliable generation: precise conditioning and guidance, preservation of faces, identity, text, and scene structure, artifact detection and suppression, and consistency across frames and views.
  • Extend these methods to 3D/4D generation, including neural and Gaussian scene representations, dynamic scene reconstruction, and controllable content creation.
  • Apply the results to camera and imaging pipelines, image and video enhancement, editing and understanding, and graphics and rendering use cases on consumer devices.
  • Transfer research results into Huawei products in close collaboration with product, hardware, and software engineering teams.
  • Publish at leading conferences and journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH) and contribute to the research community.
  • Mentor interns and junior researchers, and collaborate with academic partners in Switzerland and abroad.
What we are looking for
  • PhD (or equivalent research experience) in computer vision, computer graphics, machine learning, or a related field.
  • Strong publication record in generative modeling, image or video restoration…
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