Quilt.app
Machine Learning Engineer
Quilt.app, San Francisco, California, United States, 94199
At Quilt, we're using LLMs and other AI tools to automate the future of technical selling.LLMs are capable of miracles, but without careful control and context they are just token-vomiting parrots.As a Machine Learning Engineer, you will use state of the art models and techniques to build the intelligence behind Quilt.What You Will Do
Fine tune embeddings and LLMs for better search, RAG, and question answeringPrompt engineer RAG and other systems for question answering, data mining, and other tasksCollect analytics and mine them for product insightsBuild search and recommender systems to automatically improve the product over timeBuild real-time LLM experiences using optimizations and tricks to provide results to users faster than they are used toQualifications
Experience using LLMs to solve real world problems3+ years experience training and fine tuning ML models in productionProficiency in Python, NumPy, PyTorchAttention to detail, willingness to debug data quality issues and solve learning problems end to endPreferred: Product ML experience building recommender systemsPreferred: Additional proficiency in TypeScript, Rust, C++
#J-18808-Ljbffr
Fine tune embeddings and LLMs for better search, RAG, and question answeringPrompt engineer RAG and other systems for question answering, data mining, and other tasksCollect analytics and mine them for product insightsBuild search and recommender systems to automatically improve the product over timeBuild real-time LLM experiences using optimizations and tricks to provide results to users faster than they are used toQualifications
Experience using LLMs to solve real world problems3+ years experience training and fine tuning ML models in productionProficiency in Python, NumPy, PyTorchAttention to detail, willingness to debug data quality issues and solve learning problems end to endPreferred: Product ML experience building recommender systemsPreferred: Additional proficiency in TypeScript, Rust, C++
#J-18808-Ljbffr