AI Vision R&D Engineer for Public Safety Prototypes

Singpass; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

HTX is Singapore's Science and Technology agency focused on developing transformative, operational AI solutions for public safety. The AI R&D Engineer / Lead Engineer role involves researching computer vision and AI tech, translating findings into proofs-of-concepts, and collaborating with multi-disciplinary teams across agencies.

The candidate will conduct horizon scanning, benchmark state-of-the-art methods, and drive dataset collection, model training, and evaluation for real-world Home Team

Qualifications

• 4 to 5 years of relevant experience, with at least 2 to 3 years of hands‑on experience in AI research and application development.
• Experience with open‑source AI frameworks such as OpenCV, PyTorch, ONNX, TensorRT, and TensorFlow.

Responsibilities

• Conduct horizon scanning and landscape studies for AI technologies relevant to Home Team use cases.
• Replicate state‑of‑the‑art solutions and benchmark against internal/external solutions.
• Drive dataset collection and annotation; train and evaluate models to validate research directions.
• Collaborate with Institutes of Higher Learning and vendors to co‑develop AI solutions.
• Integrate research outcomes into operational ecosystems supporting Home Team use cases.
• Translate findings into proofs‑of‑concepts, prototypes, and demos for stakeholders.

Skills

AI research

Vision models

Python

Model training

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Tools

OpenCV

PyTorch

ONNX

TensorRT

TensorFlow

Job description

HTX is Singapore's Science and Technology agency focused on developing transformative, operational AI solutions for public safety. The AI R&D Engineer / Lead Engineer role involves researching computer vision and AI tech, translating findings into proofs-of-concepts, and collaborating with multi-disciplinary teams across agencies.

The candidate will conduct horizon scanning, benchmark state-of-the-art methods, and drive dataset collection, model training, and evaluation for real-world Home Team