Senior Machine Learning Engineer, Handwritting Recognition and Synthesis Remote

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

Take ownership
—Take responsibility with bold decision-making and bias for action

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 handwriting recognition in multiple languages, 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 the cross-functional engineering team, turning state-of-the-art research into a real product impacting the lives of millions of users. They’re a very international team, with your future coworkers being based in 5 different countries across Europe and Asia. However, due to the asynchronous nature of working that Goodnotes has adopted, any time difference will not impact your work-life balance. During the natural overlap of hours within the team, you will have daily standups to coordinate between designers, ML and software engineers, QAs to review any blockers. You can learn more about what the team does in this blog article.

About the role:

This is the role for you, if you’re excited to work on any of the things listed below:

• Develop, scale, and maintain machine learning applications to enhance the experience of millions of our users.
• Fine-tune Handwritting Recognition and Synthesis to create innovative AI-first user interfaces in Goodnotes.
• Develop dynamic interfaces for question answering, information retrieval, and chatbot functionalities over freeform handwritten and PDF documents.
• Collaborate closely with a multidisciplinary team, including engineers, QA, and product designers, in a fast-paced environment to deliver features rapidly.

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

• Demonstrable experience in building and deploying machine learning systems at scale in production environments.
• Experience with generative models, including but not limited to text generation, image diffusion, and handwriting synthesis.
• Strong grasp of computer science fundamentals with a robust background in software engineering.
• Proficiency with machine learning frameworks such as TensorFlow or PyTorch.
• Experience with any of the following big data technologies: Pinecone, Milvus, ElasticSearch, LangChain, CoreML, HuggingFace, AWS.
• Deep expertise in one or more of the following ML subfields: classical and neural information retrieval, vector search, question answering, language models.
• Mastery in Python and at least one of the following programming languages: Java, Kotlin, Swift, or C++.
• Excellent communication skills and one of the following languages: Chinese, Japanese, Korean, Thai
• A genuine interest in advancing innovation in education.