Machine Learning Researcher – Fresh Graduates are welcome

Our Values:

Dream big
—Be visionary, strategic, and open to innovation

Build great things
—Work in service of our users, always improving and pushing higher

Operate as an owner
—Propel company success and impact with an entrepreneurial mindset

Win like a sports team
—Be trusting and collaborative while empowering others

Learn and grow fast
—Never stop learning and iterate fast

Share our passion
—Share ideas and practice enthusiasm and joy

About the team:

After our huge success with the latest AI releases, we are accelerating the research and development of cutting-edge features leveraging AI to create the best learning and note-taking platform. You will be part of a cross-functional engineering team, doing state-of-the-art research that transforms into real-world products, empowering millions of users in their study/work flows. We are a globally-distributed team spanning across Europe and Asia. Thanks to the asynchronous working culture Goodnotes has adopted, time zones will not impact your work-life balance. During the natural overlap of hours within the team, you will have regular meetings to coordinate work between members on the team.

About the role:

This is an entry-level research position designed for a high-potential engineer eager to dive into Document AI. You will:

• Contribute to the development of AI/ML models that impact millions of users.
• Support research in document analysis, including Handwriting Recognition, Synthesis, and Layout Analysis.
• Collaborate closely with a multidisciplinary team, including engineers, QA, and product designers, in a fast-paced environment to deliver features rapidly.
• Bridge the gap between academic research and production-ready code.

The skills you will need to be successful in the above:

• Relevant educational background such as Computer Science, Physics, or others with strong grasp of Data Structures & Algorithms.
• A solid understanding of Machine Learning fundamentals (i.e. CNNs, RNNs, Transformers, BERT, LSTM, etc).
• Exposure to Large Language Models (LLMs).
• Research track record via publications and/or open-source contributions in Document AI or relevant fields.
• Proficiency in Python and at least one Machine Learning framework such as PyTorch, TensorFlow and JAX.
• Working knowledge of C++, Rust or Swift is a plus.
• As a distributed team, being able to articulate your ideas clearly in writing and speech is essential.

Even if you don’t meet all the criteria listed above, we would still love to hear from you! Goodnotes places a lot of value on learning and development and will support your growth if needed.

The interview process:

• An introductory call with someone from our talent acquisition team. They want to hear more about your background, what you are looking for, and why you’d like to join Goodnotes
• A short Algo/Data structure interview with an Engineer
• An ML technical interview with one of our ML engineers. This is where you get to see what it would be like working at Goodnotes as well as the chance to ask any questions you may have about our ML R&D
• A call with your hiring manager. This is the person who will be managing you day to day, working on your growth and development with you as well as supporting you throughout your career at Goodnotes
• Values interview to align with the company culture with a few team members of the team you would be joining or a member of the leadership team.

What’s in it for you:

• Meaningful equity in a profitable tech-startup
• Budget for things like noise-cancelling headphones, setting up your home office, personal development, professional training, and health & wellness
• Sponsored visits to our Hong Kong or London office every 2 years, and yearly offsite
• Company-wide annual offsite
• Flexible working hours and location
• Medical insurance for you and your dependents