Knowtions Research is an applied AI company on a mission to insure the next billion people. We work with insurers to pioneer digital Pay-How-You-Live insurance products using Lydia AI, our risk prediction engine. Lydia AI leverages new sources of data to make dynamic health predictions to create insurance products focused on keeping people healthy rather than paying when people get sick.

We are a Canadian company targeting the fastest growing insurance markets in Asia and are backed by investors including Information Venture Partners and Alibaba Entrepreneur Fund.

Join us to help insure the next billion people.

As an ML Engineer, you would be responsible for training, testing, and deploying our data science pipeline: from data extraction and transformation to modelling this data so that it can be efficiently served via our APIs. We are looking for an experienced ML engineer who will bring subject matter expertise and best practices to all aspects of working with big data and bringing models into production.

This is a full-time role in Taipei, Taiwan.

Qualifications:

• Eager and able to learn quickly. You have a devotion to evaluating and appropriately applying emerging and alternative technologies, languages, frameworks, and platforms.
• You are committed to collaboration and thrive working across inter-disciplinary groups, including data science, engineering, product, and management, to build great products.
• You have a way of speaking, writing, and relaying information that engages people and expresses appreciation for diverse opinions and approaches.
• Care about improving healthcare using the latest in machine learning and artificial intelligence
• Own problems end-to-end in a very ownership driven culture
• Care more about reviewing and adopting industry wide data science practices to solving problems as opposed to writing a lot of code
• Comfortable massaging and cleaning up datasets for loading
• Comfortable interacting with clients to understand requirements and pain points
• Comfortable interacting with clients to discuss models, training, metrics, data analytics and general statistics on data
• Comfortable interacting with clients and partners to discuss high-level system architecture, system integration and deployment

Requirements

• Familiarity with architecting and designing high performance server-side components and big data processing pipelines using popular libraries and frameworks
• Experience with Tensorflow (or similar libraries) from GPU training, efficient input pipelines (queues, Dataset API, and the like), to deployment of packaged/compiled models, and distributed computing (sharding, clusters, etc.)
• Experience resource management service workflow: queue systems (RabbitMQ, Kafka), AWS (RDS, S3, Kubernetes), and Docker.
• Experience with data technologies Postgres, Pandas, Numpy
• Experience with data exploration
• Experience with developing production code in Python, Node.js, Java/Scala or C/C++
• BSc in Computer Science or a quantitative field and at least 1 year of industry experience.
• Preferably bilingual or some proficiency (English and Chinese)

In a typical week, you might...

• Resolve performance issues with various aspects of the pipeline and application
• Improve ML models several times over
• Automate various components of the training/test pipelines and model deployments
• Importing new clinical data to work with our internal ontologies