Senior Machine Learning Engineer, AI Product and Platform

BetterUp is a company focused on human transformation through world-class coaching and Generative AI. They are seeking a Senior Machine Learning Engineer to prototype and evaluate LLM-powered features, manage the production lifecycle, and collaborate with various teams to enhance user experiences. Responsibilities: Prototype, fine-tune, and evaluate LLM-powered features—from conversational insights to practice-moment nudges—using Python and Jupyter notebooks; Own the production lifecycle: data prep, experiment design, offline/online evaluation, and weekly pushes to prod alongside a tight squad of ML/Backend/Full Stack Engineers; Collaborate daily with Product, Coaching Science, and Learning Design to turn behavior-change research into delightful user moments; Contribute to technical design by shaping model architectures, retrieval strategies, and safety guards—while staying hands-on in code; Measure what matters: define success metrics, implement A/B tests, and iterate quickly on real coach feedback; Ship end-to-end improvements to products like FocusFrame, our AI copilot that helps coaches deliver higher-impact sessions in real time Qualifications: 4+ years building and shipping ML systems in production, with at least 6–12 months hands-on with LLM fine-tuning, prompt engineering, or RAG pipelines; Fluency in Python for AI development and comfort working in Jupyter/IPython; Solid understanding of modern ML tooling (e.g., PyTorch, TensorFlow, or JAX) and containerized/cloud deployment basics; Clear, approachable communication with both technical peers and non-technical partners; Bias toward action, curiosity, and comfort navigating ambiguity in a fast-moving startup environment Required Skills: Machine Learning Systems, Large Language Model (LLM) Fine-tuning, Prompt Engineering, Retrieval-Augmented Generation (RAG) Pipelines, Python, Jupyter/IPython, PyTorch, TensorFlow, JAX, Containerized Deployment, Cloud Deployment, Curiosity, Bias toward action, Comfort navigating ambiguity