Senior Software Engineer - Machine Learning, LLM
June 24
🏢 In-office - London
Description
• This is the role for you, if you’re excited to work on any of the things listed below: - Developing and scaling machine learning applications to tens of millions of users - Building conversational RAG systems for question answering, summarization, and self-learning over handwritten and PDF documents - Building a novel platform using GenAI to radically transform how people study and work - Fine-tuning and prompting large language models to build an AI-first user experience GoodNotes - Working in a fast-paced, multidisciplinary squad with engineers, QA, product designers to rapidly ship features • Even if you don’t meet all the criteria listed above, we would still love to hear from you! Goodnotes places a lot of value on learning and development and will support your growth if needed.
Requirements
• Hands-on experience in building and deploying machine learning systems at scale in production • Strong experience with RAG systems and agentic workflows with LLMs, preferably with some experience with multimodal LLMs • Strong understanding of computer science fundamentals and a solid background in software engineering • Experience with any of the following software ecosystems: vector databases (eg. Pinecone, Milvus), ML platforms (eg. Metaflow, ClearML), cloud ML providers (AWS / Azure, GCP), LLM frameworks (eg. LangChain/LlamaIndex), HuggingFace, CoreML • Deep knowledge in one or more of the following ML subfields: classical and neural information retrieval, vector search, question answering, transformer-based language modeling • Mastery in Python and at least one of the following programming languages: Java/Swift/C++ • Interested in advancing innovation in education
Benefits
• 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
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