Senior Machine Learning Engineer, Education Goodnotes. We want to make work and study more efficient and enjoyable, by providing the best digital paper solution possible. We plan to be the go-to tool for all forms of notes. Our digital paper and learning ecosystem inspires anyone to take notes, share what they know, collaborate with others, and learn as a community. 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. Be user obsessed. —Empathetic, inquisitive, practical. . . 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:. Opportunity to work on creative problems to solve real life problems. Develop, scale, and maintain machine learning applications to enhance the experience of millions of our users.. Develop dynamic interfaces for generative AI as well as classical machine learning.. 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:. Must-Haves:. Demonstrable ML experience, either via. Education (CS/Math/Physics/ML) and/or publications in relevant fields. Industry Experience in building and/or deploying machine learning systems. Open-source ML projects (author or major contributor). Strong grasp of computer science fundamentals with a robust background in software engineering.. Proficiency in Python or Julia. Excellent communication skills in English. Nice-to-have. Proficiency with machine learning frameworks such as TensorFlow or PyTorch. Working knowledge or fluency in either of Chinese, Japanese, Korean, Thai. Working knowledge of Java, Kotlin, Swift, or C++ is a plus.. Experience with any of the following big data technologies: Pinecone, Milvus, ElasticSearch, LangChain, CoreML, HuggingFace, AWS.. 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. ML Background Assessment Interview: They want to hear about your experience to assess your suitability for this role.. CS fundamentals + Coding Interview: This is one of the technical interviews to assess your grasp over fundamental concepts in Computer Science as well as practical coding.. 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. Eventual interview with Leadership based on seniority. What’s in it for you:. Meaningful equity in a profitable tech scale-up. 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.
Senior Machine Learning Engineer, Education at Goodnotes