APOIDEA is an AI fintech company which leverages novel techniques in deep learning and natural language processing to extract insights within and among financial texts.
We are actively serving financial institutions in Hong Kong and Singapore, which includes various applications in commercial lending, wealth management and securities brokerage.
We are looking for a Machine Learning Engineer to optimize the machine learning systems of our document intelligence solutions to reinvent business processes in the finance industry and develop future state products.
A typical day is like :
Convert a prototype into a scalable machine learning system;
Profile a machine learning system and optimise latency, which includes request batching, model optimization;
Develop different machine learning training and evaluation workflows;
Maintain machine learning gateway such as rate limit, logging, cache layer and etc.;
Cooperate with DevOps team on auto scaling mechanism so as to reduce operational cost;
Promote and maintain excellence and best practices across machine learning and software engineering teams regarding machine learning implementation and system design;
Challenges we are facing :
Orchestration of more than 20 models;
Maintaining latency requirement without sacrificing model accuracy and server cost;
Ever-increasing expectation of model quality;
Working with cutting-edge technologies.
Who is our ideal candidate :
Degree holder or above in Computer Science, Information Engineering, Mathematics, Statistics, Physics or relevant disciplines;
Excellent knowledge of high performance computing frameworks in Python and language (C++, Go);
Experience in building pipelines / workflow as Directed Acyclic Graph (DAG);
Knowledgeable in machine learning framework such as scikit-learn and PyTorch;
Strong interpersonal and communication skills, positive work attitude, self-motivated and be a team player;
Good command of written and spoken English
What we offer :
A friendly and flat start-up culture which emphasizes rapid experimentation and learning;
A dynamic team with international background;
A rapid growing and expanding startup environment;
External learning sharing culture;
Free flow of snacks and drinks;
Regular team activities, casual wear on working days.