Our client, a leading Insurance Company, is looking for a Machine Learning Engineer with their Innovation Technology team to build end-to-end ML solutions for Data Science. The selected candidate will be leading their Machine Learning capabilities by building solutions to analyze distributed data sets and robust results predictions. This role will be a key person in leading the ML function for Data Analytics across the firm.

Responsibilities:
– Build Machine Learning solutions in deploying analytics models with different production environments.
– Enable ML solutions in analyzing distributed data sets and robust data prediction results.
– Work with the business teams in understanding the business problems where ML can step in and provide solutions.
– Build ML solutions and standards across the business and technology in the organization.
– Work with the senior leaders in defining the technology strategy, solutions, and architecture in data analytics and data science.
– Provide SME advice to the analytics team on how to adopt Machine Learning solutions to solve complex data sets and analytics.

Requirements:
– At least 5years of working experience in software development, data analytics, or AI/ML areas.
– Experience in building cloud-based machine-learning solutions.
– Software development experience in Python. Modern deep learning libraries such as HuggingFace, PyTorch, and TensorFlow.
– Knowledge in designing and implementing data infrastructure on Public Cloud infrastructures like AWS, Azure, or GCP.
– Working knowledge of Machine Learning, Deep Learning, and Graph Analytics (say Noel4J, GraphX).
– Strong knowledge and experience in Data warehouse and relational databases.
– Strong knowledge and experience in NoSQL DBs.
– Strategic thinking and communication, which is able to coach and lead all levels of people.
– Strong leadership and influencing skills.
– Bachelor’s degree from a reputable University.
– Excellent communication skills in English and Cantonese.

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