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:
-
Design and implement speech foundation models and speech language models
(SLMs) for a variety of applications
-
Develop algorithms for speech and acoustic signal processing, including ASR,
speech enhancement, beamforming, and acoustic event detection
-
Conduct original research and prototyping using deep learning, transformers,
RNNs, and other modern machine learning techniques
-
Collaborate closely with cross-functional teams to bring speech-related
solutions from concept to integration into real-world systems
-
Evaluate and benchmark algorithms using both quantitative metrics (e.g., WER,
PESQ, STOI) and qualitative assessments
-
Develop robust infrastructure and pipelines to support rapid experimentation
and deployment of research ideas
-
Stay at the forefront of developments in speech technology, foundation
models, and conversational AI, and incorporate state-of-the-art methods into
research and product development
About the ideal candidate:
-
Ph.D. in Computer Science, Electrical Engineering, or a related field with a
strong focus on speech processing and machine learning
-
Demonstrated experience with LLMs, ASR systems, and modern speech models
(e.g., Whisper, wav2vec, HuBERT, Conformer)
-
Proficiency in Python and experience with at least one additional programming
language (e.g., C++, Java, JavaScript)
-
Expertise in deep learning frameworks such as PyTorch, TensorFlow, or Keras
-
Familiarity with common audio/speech processing libraries (e.g., TorchAudio,
Librosa, PyAudio)
-
Strong grasp of digital and statistical signal processing, including spectral
and spatial filtering
-
Experience working with large-scale, noisy datasets in real-world
environments
-
A solid publication record in relevant venues (e.g., NeurIPS, ICML, ICLR,
Interspeech, ICASSP, AES)
