Applied Scientist

Are you excited to be part of a dynamic, research-focused startup environment?Do you have a strong interest in generative AI and large language models?Would you like to join a forward-thinking team developing advanced AI solutions, across language and vision-based modeling?We're partnered with an interesting early-stage AI company developing intelligent systems designed to automate tasks typically requiring human expertise. They're advancing cutting-edge solutions powered by state-of-the-art language (LLMs) and vision models (VLMs) to solve real-world, complex practical problems. As part of the founding team you'll play a pivotal role in shaping the future of AI and building technologies that have a huge real-world impact.Responsibilities Extract structured and unstructured data with precision from a variety of document types.Create systems that identify AI errors and escalate them for human review.Develop autonomous agents capable of navigating websites and completing forms independently.Design a rule engine that interprets and validates data using natural language rules.Requirements:4+ years of ML experience building and deploying LLMs. Strong research background with publications in top ML conferences (e.g., NeurIPS, CVPR, ACL, EMNLP, etc).A strong passion for rapid iteration and building innovative solutions (talent in this area is highly saught after)Experience improving LLM/VLM accuracy and reliability.Skilled in fine-tuning foundation models and deploying them in production.Expected to keep up-to-date with the latest AI advancements/ trends and discuss and implement where necessary.Please apply if interested.Big Cloud is a leading recruiter in the AI & Data Science space. We're lucky enough to recruit the best candidates in partnership with some of the most exciting companies all over the world. We try to reply to all applications, but we're only human, for now! So, you may only hear from us if you are successful.Check out our latest vacancies to see what else we're recruiting for:

Created: 2025-01-31