Machine Learning Engineer, Coach Platform

Join to apply for the Machine Learning Engineer, Coach Platform role at Motive Software

Machine Learning Engineer, Coach Platform

Join to apply for the Machine Learning Engineer, Coach Platform role at Motive Software

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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 Do

• 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.
  
  

• 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.
  
  

• Prior experience in coaching, learning-science, ed-tech, or behavior-change domains.
• Exposure to RLHF, preference tuning, or multimodal models.
  
  

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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