Engineer / Senior Engineer - Edge Analytic & Learning

Our client is a trailblazing pioneer in the Tobacco Manufacturing Industry. What sets them apart is their unwavering commitment to innovation and progress. They have embarked on a remarkable journey of transformation, with a resolute aim to create a smoke-free future. This ambitious endeavour has completely redefined every aspect of their business, from the production and distribution of their products, to how they interact with their customers and society as a whole.

By embracing this transformation, our client is leading from the front, with their pioneering vision and steadfast determination to create a smoke-free future.

With a workforce of more than 75,000 talented individuals worldwide across 180 countries, they have truly established themselves as a global leader in the industry. 

Responsibilities:

• To work with other stakeholders to design the data required for learning the device & user behaviors.
• To mine & analyze the data available to understand the device and user behaviors. 
• To work with IoT cloud and data analytic teams to distribute the computation resource between cloud and edge. 
• To provide the best approach for the target applications, to train and implement the model into the edge device.
• To continuously improve the model to enhance the user experience & device productivity.
• To closely tracking the R&D results and to work with research institutions for projects.

Requirements:

• University degree (MSc, MPhy or PhD) in data science, machine learning, statistic. Priority will be given to candidates with major in any of the 2 subjects.
• 3+ years experience in data analytic or machine learning for IoT applications, e.g. automatic temperature control for smart thermostats, predictive device maintenance, etc.
• Solid knowledge in mathematics, statistic & probability.
• Solid experiences in data labelling, statistical modelling (regression, clustering), supervised & unsupervised learning, DNN models for different applications.
• Solid experiences in identifying valuable data, data collection method, processing of structured and unstructured data, mining trends & pattern from data, predictive modelling.
• Strong mindset of real-time implementation, to ensure the algorithm developed is realistic for real-time & scalable applications.
• Hands on experience in coding with Python, R, Java, C++.
• Hands on experience in software tools, such as TensorFlow, PyTorch, Keras, Caffe, Spark, Hadoop, Hive, NoSQL.
• Strong analytical & innovative mindsets, strong system debug skill, thinking positive, be bumble & open-minded.
• A stakeholder in edge computing for the FW team and a good team player.
• Good command of English and communication skill.