Huawei Canada has an immediate permanent opening for a Senior Researcher.
About the team:
The Human-Machine Interaction Lab unites global talents to redefine the
relationship between humans and technology. Focused on innovation and
user-centered design, the lab strives to advance human-computer interaction
research. Our team includes researchers, engineers, and designers collaborating
across disciplines to develop novel interactive systems, sensing technologies,
wearable and IoT systems, human factors, computer vision, and multimodal
interfaces. Through high-impact products and cutting-edge research, we aim to
enhance user experiences and interactions with technology.
About the job:
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Design, develop, train, evaluate, and optimize advanced Computer Vision, and
Machine Learning models, and, Vision-Language models (e.g., transformers,
multimodal encoders, diffusion models), emphasizing on-device performance and
efficiency
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Prototype and optimize SOTA architectures for tasks such as image
understanding, visual search, object detection, segmentation, multimodal
grounding, etc.
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Implement Computer Vision and Machine Learning algorithms from scratch or
leverage existing libraries and frameworks (e.g., TensorFlow, PyTorch,
scikit-learn, Keras)
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Explore and apply techniques such as quantization, pruning, distillation,
LoRA adapters to meet mobile/embedded constraints
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Choose appropriate algorithms and techniques based on problem requirements,
data characteristics, and business needs
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Manage and process large datasets, including cleaning, pre-processing, and
transformation
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Build and maintain data pipelines for model training and inference
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Deploy Machine Learning models to production environments and maintain model
retraining and versioning strategies
About the ideal candidate:
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Ph.D. or Master's degree in Computer Science or a related field with a focus
on Computer Vision and Machine Learning
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Minimum 3 years of Computer Vision and Machine Learning research and
development experience, with a strong portfolio of applied projects or
publications
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Proficiency in Computer Vision and Machine Learning frameworks (e.g.,
TensorFlow, PyTorch), and modern CV toolchains (OpenCV, MMDetection,
Detectron2, etc.)
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Familiarity with transformers, diffusion models, contrastive learning (e.g.,
CLIP, ALIGN), and prompt/adaptor-based fine-tuning techniques is an asset
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On-device model deployment experience is an asset
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Experience contributing to relevant open-source projects is an asset
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Experience building commercial agent/conversational systems is an asset
