The future of education is already here – it's just not evenly distributed. Join us now to bridge the gap between individual and collective intelligence. Take the lead of our ML engineering team to build a content discovery platform that encourages users to find their inspiration through learning and exploration. More than an Apple-featured App loved by million notetakers, let's create the future of learning together.
What you will achieve in this role
Make GoodNotes platform the epicenter for sharing and transferring knowledge
Design, build and deploy large scale note-sharing search/recommendation systems to serve millions of users
Identify and evaluate new ideas to tackle edge cases ranging from data collection to model development
Research new models and productionize solutions at scale from academic and industry knowledge
Work in a product-driven environment with quick iteration turnaround to get continuous feedback
Collaborate with product and design teams to identify opportunities to improve our content discovery
Promote best practices for managing the ML lifecycle inside the team
What you need to be successful
Hands-on experience in building end-to-end search and/or recommender systems at scale in production
Love for writing efficient and maintainable code
Strong understanding of computer science fundamentals and a solid background in software engineering
Familiarity with one or more distributed ML frameworks: TensorFlow, PyTorch, XGBoost, LightGBM, Spark MLlib
Experience with two or more of the following big data technologies: Hadoop, Spark, Hive, Kafka, Cassandra, Redis, Beam, Elasticsearch
Deep knowledge in one or more of the following ML subfields: Information Retrieval, Recommender Systems, Natural Language Processing. Good to have knowledge in: Reinforcement Learning, Graph Representation Learning, Social Network Analysis
Mastery in at least two programming languages: Java/Scala/C++ and Python
Ability to design and execute an R&D roadmap
Good taste as a maker
Interested in advancing innovation in education
Less experienced candidate will be considered as Machine Learning Engineer.
Apply Now:
• You'll receive a competitive compensation and meaningful equity along with a chance to make significant contribution to a product people already love.
• Most of our positions are eligible for remote work, provided you have at least 3 hours of overlap with the team in the office every weekday between 10 AM and 6 PM. Please indicate your preference in your application form.
• You're also welcome to join us in our Hong Kong or London office, we sponsor visas and relocations.
• We take care of you and your loved ones with medical insurance and flexible working hours including two optional work-from-home days!
• Join our best company tradition, the annual off-site. Check out our pictures from team outings and more on our Instagram.
