Let’s face it: if you’re going to build the future of human transformation, you deserve more than a paycheck.
You deserve a personal BetterUp Coach, the most curious teammates on the planet, and a mission that pulls you out of bed every morning. At BetterUp, we pair world-class coaching with Generative AI to help millions live with clarity and purpose. Ready to engineer the models that make that magic feel personal?
What you’ll doPrototype, 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.
Core
3–5 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.
Bonus (nice-to-have, not required)
Prior experience in coaching, learning-science, ed-tech, or behavior-change domains.
Exposure to RLHF, preference tuning, or multimodal models.
Not sure you hit every bullet? We value growth mindsets—please apply anyway.
Apply Now