Job description
At Goodnotes, we believe that every individual holds untapped potential waiting to be unleashed. By reimagining the way we interact with information, we’re merging human creativity with the breakthrough capabilities of AI. Our renewed vision and mission drive us to create the best medium for human and AI collaboration, empowering users to explore new dimensions of productivity, creativity, and learning. Join us on this journey as we transform digital note-taking into an inspiring and innovative experience.
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 like an owner
—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 that impacts the lives of millions of users. They’re a very international team, with your future coworkers being based in 6 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 collaborate with designers, ML and software engineers, QAs to review any blockers.
About the role:
This is the role for you, if you’re excited to work on any of the things listed below:
- Developing and scaling agentic and multimodal AI systems to tens of millions of users
- Developing and scaling an advanced RAG system for question answering, summarization, self-learning, and AI coediting over handwritten and PDF documents
- Building a novel medium combining multimodal LLMs and freeform notetaking technology to radically transform how people engage with their information
- Productionizing LLM pipelines to build an AI-first user experience GoodNotes
- Working in a fast-paced, multidisciplinary squad with engineers, QA, product designers to rapidly ship features
The skills you will need to be successful in the above:
- Demonstrated academic excellence in a BSc or MSc in Computer Science, Electrical Engineering, Mathematics, or related fields
- Internship(s) or substantial side project(s) in generative AI (e.g., fine-tuning small LLMs, RAG, prompt-engineering chatbots, etc.)
- Professional fluency in Mandarin Chinese and English – able to read technical papers, write documentation, and communicate with cross-regional teams
- Solid grounding in data structures, algorithms, and software engineering best practices
- Proficient in Python for ML/AI prototyping
- Exposure to at least one additional language (e.g., Java, Swift, or C++) – coursework or hobby project is acceptable
- Comfort using Git and containerizing projects with Docker
- Deployed at least one personal or school project to a public cloud (AWS / GCP / Azure) or platform-as-a-service (e.g., Render, Vercel)
- Basic understanding of transformer internals and how attention mechanisms scale
- Eager to pair with senior engineers, give & receive feedback in code reviews, and iterate quickly
- Evidence of self-learning (courses, Kaggle comps, open-source contributions)
Skills that are preferable but not required (you’ll learn the rest here):
- Coursework or hackathon experience with multimodal LLMs (text-to-image, speech, vision-language)
- Exposure to Kubernetes or serverless frameworks for hobby deployments
Why This Role Is Junior-Friendly
We designed this spec so that motivated graduates can grow into full-stack AI engineers under mentorship. If you bring strong fundamentals, proven curiosity through internships or projects, and bilingual communication skills, we’ll help you master large-scale deployment, agentic workflows, and advanced model optimization on the job.
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
3 60-minute Technical interviews:
- A short Algo/Data structure live-coding interview with an Engineer
- An exploration of your course/project experience with AI. 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 technical interview on NLP and LLMs
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
A 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
Note: Employment is contingent upon successful completion of background checks, including verification of employment, education, and criminal records.
Note: Employment is contingent upon successful completion of background checks, including verification of employment, education, and criminal records.
