Co-op Researcher – Multimodal & Voice Interaction (HCI)

Huawei Technologies Canada Co., Ltd.•Markham, ON

23h

About The Position

Huawei Canada has an immediate co-op opening for a Researcher. 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.

Requirements

Currently pursuing a Bachelor’s degree in Computer Science, HCI, or a related field, and enrolled in a co-op program.
Solid understanding of data structures and algorithms, including the ability to reason about time/space complexity and choose the right structure for the task.
Strong coding skills in at least two of: Python, C++, Java, C#, Kotlin – experience writing programs of several hundred lines independently.
Exposure to voice/speech or AI concepts (e.g., speech recognition, chatbots, or basic machine learning).
Familiarity with at least one ML framework (e.g., PyTorch, TensorFlow) and basic model inference workflow (e.g., loading a model, running inference, post‑processing).
Experience with at least one platform (e.g., Windows, Android, or Linux) – comfortable debugging, using command line, and managing dependencies.
Strong problem‑solving and troubleshooting skills – able to unblock themselves on straightforward issues before asking for help.
Genuine interest in building intelligent voice‑driven interfaces and exploring how speech integrates with other modalities.

Responsibilities

Build simple prototypes (applications or small services) that demonstrate voice-first multimodal interactions (e.g., voice + touch, voice + gesture) on real devices.
Use existing speech tools (e.g., Whisper, Vosk, or similar) to integrate features like speech recognition or text-to-speech.
Perform light tuning and testing to improve responsiveness and usability.
Work with inputs such as audio, camera, and touch to implement straightforward interaction logic (e.g., combining voice commands with simple gestures or confirmations).
Collaborate with researchers and designers to prototype new interaction ideas (e.g., conversational interfaces, voice commands).
Help translate concepts into testable demos.
Use common tools and frameworks (e.g., PyTorch, TensorFlow).
Learn how different tools are used for on-device vs. cloud-based solutions.
Write clean and readable code.
Run small tests (e.g., latency or usability checks) and document what you learn.