Machine Learning Engineer, LLM

Key Skills

AWS, C++, CoreML, Data structuring, Elasticsearch, Generative models, HuggingFace, Java Programming, Kotlin, LangChain, Large Language Models - LLMs, Machine learning techniques, Milvus, Pinecone, Python Programming, PyTorch, Swift, TensorFlow

Job Description

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. 

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 and prompt-tune LLMs 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.
• Expertise in large language models and transformers.
• 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++.
• A genuine interest in advancing innovation in education.

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