Job Description

Own end-to-end ML workflows from data ingestion to production deployment. You will dive deep into core application domains like price prediction, two-sided market design (ranking/recommendations), or agentic workflows using state-of-the-art LLMs. A key part of your role will be establishing and enforcing MLOps and LLMops best practices. You have: 5+ years of ML engineering experience, with at least one year working with LLMs. You possess strong Python skills, a proven track record of deploying containerized services (Docker, Kubernetes), and deep expertise in at least one of the following: deep learning (PyTorch, Transformers), ranking/matching algorithms, or LLMops (RAG, evals, fine-tuning).