Senior AI Engineer, Goodnotes

• Hands-on experience in building and deploying AI applications at scale in production
• In-depth LLM experience with either RAG or agentic workflows
• Good understanding of computer science fundamentals
• Mastery in Python and at least one additional programming languages for full-stack engineering (eg. Java/Swift/C++)
• Solid experience with most of the following software ecosystems and technologies in full-stack engineering:
• Cloud platforms and serverless computing (e.g., AWS Lambda/ECS/SageMaker, Google Cloud Run/Cloud Functions)
• Containerization and orchestration (eg. Docker, Kubernetes)
• Vector databases (e.g., Pinecone, Milvus, Weaviate)
• ML experimentation and model management platforms (e.g., MLflow, Weights & Biases, ClearML)
• LLM providers and AI services (eg. AWS Bedrock, Azure OpenAI Service, Google Vertex AI)
• Open-source AI community platforms and frameworks (eg. HuggingFace, LangChain, LlamaIndex)
• API development frameworks (eg. Python FastAPI, Flask)
• Openness to work across API logic level and infrastructure level

Desirable

• 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 based in 6 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
• 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

• 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 interview with an Engineer
• An exploration of your work 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