Research Engineer (in AI-Assisted Speech Therapy) - ZZC

Description

OverviewAs a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills that are relevant to industry demands while working on research projects in SIT.

The primary responsibility of this role is to contribute to an applied research project related to AI‐assisted speech therapy in collaboration with hospital partners.

Key ResponsibilitiesModel Development :

Design, train, and fine‐tune ASR and TTS models to achieve high accuracy and personalization across diverse speech patterns and impairments.

Data Management :

Oversee data collection and preprocessing in collaboration with healthcare partners to ensure quality, diversity, and clinical relevance.

System Integration :

Export and deploy models for real‐time use on mobile and web platforms, and work with developers to ensure seamless integration.

Tooling and Automation :

Develop pipelines and utilities to support data processing, model training, evaluation, and continuous improvement.

Collaboration and Knowledge Transfer :

Document technical processes, contribute to multidisciplinary teamwork, and guide students in applied research and system development.

Job RequirementsEducational Background

Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Master's degree is preferred.

ASR / TTS Expertise

Experience in training and fine‐tuning Automatic Speech Recognition (ASR) or Text-to-Speech (TTS) models, preferably in multilingual or speech impairment contexts.

Programming Skills

Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with web development (e.g., FastAPI, Flask, or React) is a plus.

Data Handling

Familiarity with speech data collection, preprocessing, and management to ensure quality and ethical data use.

Deployment Knowledge

Experience exporting and deploying models on cloud or cross‐platform environments.

Collaboration and Communication

Strong teamwork, documentation, and communication skills to work effectively with multidisciplinary teams and healthcare partners.

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