Speech AI Engineer (Healthcare)

AI Singapore (AISG) is Singapore's national programme in artificial intelligence, launched by the National Research Foundation (NRF) to anchor deep national capabilities in AI. Hosted at Nanyang Technological University (NTU), AI Singapore brings together Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies to perform use-inspired research, grow knowledge, create tools, and develop the talent to power Singapore's AI efforts. Since our inception in 2017, we have established a culture of respect, continuous learning, experimentation and curiosity, centred around innovation.

We are seeking a Speech AI Engineer (Healthcare) to shape the future of clinical technology. In this role, you will work on cutting-edge voice models, gaining exposure to both top-tier academic research and real-world medical deployment.

Key Responsibilities:

As a Speech AI Engineer (Healthcare), you will work closely with clinical partners and AI researchers at the NTU main campus. Your primary responsibilities include:

• Model Development: Build and fine-tune state-of-the-art speech recognition and audio processing models for clinical environments.

• Data Optimization: Process medical audio datasets to ensure robust performance across local demographics and complex medical terminologies.

• Clinical Collaboration: Deploy voice AI solutions, such as automated medical transcription, to alleviate administrative burdens for healthcare professionals.

• Performance Evaluation: Conduct rigorous testing and evaluation to optimize models for secure, real-time hospital deployment.

Job Requirements:

• Degree from a recognized university in Computer Science, Artificial Intelligence, Computer Engineering, or a related field.

• Proven hands-on experience building and evaluating Automatic Speech Recognition (ASR) or audio processing models.

• Strong programming proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).

• Familiarity with modern speech libraries (e.g., Hugging Face, Whisper, Wav2Vec).

• Experience with Natural Language Processing (NLP) to complement speech-to-text pipelines.

• Experience with model deployment and containerization (e.g., Docker) in real-world environments.

We regret that only shortlisted candidates will be notified.