Facilitate discussions with stakeholders to understand their business challenges, sharpen the business use cases and translate them into data
science projects.
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.
Present findings, solicit feedback and prioritise refinements to the analysis in close iteration with stakeholders while managing overall project timeline.
Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle.
Transfer technology to industry partners.
Technical engagement and collaboration with research institutes and institutes of higher learning.
Requirements:
Postgraduate or Ph.D. 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.
Proficient in building machine learning models to identify, recognise patterns
and make predictions.
Strong coding experience in programming languages such as Python, C++.
Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch.
