Key Responsibilities
- Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
- Technical assessment on the maturity, viability, and suitability of AI research, technologies and trends that are relevant to the industry
- Develop software components based on microservices-based architecture
- Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle
- Propose, implement, and validate algorithms, ensuring functional and non-functional requirements such as transparency, fairness, scalability, security, integration complexity and operational costs
- Write thought leadership articles, including blogs and papers, on AI Transfer technology to industry partners.
- Technical engagement and collaboration with research institutes and institutes of higher learning.
Requirements
- Background in engineering, computer engineering, computer science, mathematics, statistics or equivalent
- Strong technical knowledge in AI, specifically in Computer Vision (CV), Natural Language Processing (NLP), recommendation system and/or Synthetic AI
- Good understanding of the latest research and technologies in AI for production, including deployment to mobile handsets and IOT devices.
- Strong coding experience in programming languages such as Python, C++
- Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch
- Team player with the ability to work in a cross-functional team with excellent interpersonal skills.
- Strong communication skills, both verbal and written, as well as strong presentation and engagement skills
- Strong stakeholder management skills