monday.com is looking for a full-stack data scientist to join our brand new AI Assistant R&D team within the platform. You will take the lead on implementing generative AI capabilities within monday.com AI Assistant platform including defining the strategy of using LLMs, training it with proprietary data, and productizing it as part of our platform offering.

　　Monday AI team is responsible for the end-to-end capabilities of generative AI within monday.com platform, creating new capabilities and values for our users and building it in the open platform way, so every 3rd party monday.com developer would be able to use it for building their AI applications.

　　About The Role

　　monday.com is looking for a full-stack data scientist to join our brand new AI Assistant R&D team within the platform. You will take the lead on implementing generative AI capabilities within monday.com AI Assistant platform including defining the strategy of using LLMs, training it with proprietary data, and productizing it as part of our platform offering.

　　Monday AI team is responsible for the end-to-end capabilities of generative AI within monday.com platform, creating new capabilities and values for our users and building it in the open platform way, so every 3rd party monday.com developer would be able to use it for building their AI applications.

　　The optimal candidate will have proven experience developing and implementing the latest generation of generative AI models, ideally within a product or in business/analytics settings. They will have strong engineering backgrounds and business aptitude and experience modeling and optimizing processes such as user segmentation, funnel dynamics, financial scenario analysis, LTV prediction, and the like.You will be responsible for initiating, planning, and executing AI and data analytics flows from inception to fruition.Identify and pursue opportunities to incorporate generative AI within monday.com's ecosystem: within the product and as part of our application framework.Work closely with full-stack developers, product managers, data analysts, and other stakeholders within the team to build production-ready capabilities for more than 186,000 customers.

　　Your Experience & Skills

　　B.Sc. and ideally an advanced degree in a technical field such as Computer Science, Mathematics, Statistics, or equivalent experience3+ years of experience as a Data Scientist in non-academic settings, with a focus on Large Language Models, NLP or other deep learning fields; a demonstrated record of conceiving, designing, and shipping successful data science/analytics projects to production (interesting failures are also okay)Hands-on proficiency with modern generative AI models, prompt engineering, agents, and RAG architectures. Also, a solid understanding to transformers, optimized fine-tuning techniques such as LoRA, and evaluation methodologies of LLMs.Strong understanding of machine learning and deep learning algorithms and principles and familiarity with relevant frameworks (TensorFlow, PyTorch, etc.)Strong control of classic machine learning algorithms and advanced statistics; hands-on experience with Bayesian inference or causal inference - an advantageHands-on experience with LLMs-related libraries and frameworks (HF transformers, LangChain, LlamaIndex, etc) - An advantageHigh proficiency in Python- A mustPrevious knowledge in Typescript- An advantageThis is a full-stack role - an ideal candidate will not only be comfortable with algorithmic tasks and model training but also have the technical know-how to set up and operate the environment and tooling that they requireGreat communication skills, with a penchant for data visualization and storytelling