Machine Learning Scientist

Seattle, WA / Remote
🚀 About Rebo AI

At Rebo AI, we’re leveraging cutting-edge NLP, LLMs, and machine learning to create a platform that enables instant understanding and action on qualitative feedback at massive scale. Our team of ex-Microsoft and Google ML engineers - backed by leading investors - pushes the boundaries of AI every day. We’re turning static feedback into dynamic, real-time conversations between businesses and customers, shaping the future of customer experience.

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📌 About the Role

As a Machine Learning Scientist at Rebo AI, you’ll be at the forefront of building and optimizing our intelligent core. You’ll design and implement state-of-the-art ML algorithms that transform raw, unstructured data into rich, actionable insights. You will explore unsupervised learning techniques, build and fine-tune LLMs, and continuously experiment with new architectures to enhance performance and scalability.

Working side-by-side with our engineering and product teams, you’ll tackle complex NLP challenges, improve system accuracy, detect emerging issues automatically, and ensure our customers receive the most meaningful insights - instantly.

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✅ What You’ll Do
  • Research, prototype, and deploy ML models (including LLMs and unsupervised algorithms) that extract insights from massive volumes of qualitative feedback.
  • Continuously optimize model performance, scalability, and latency for real-time analysis and response.
  • Stay at the cutting edge of AI research - integrating new breakthroughs into our product roadmap.
  • Collaborate closely with product, design, and engineering teams to bring ML-powered features from concept to production.
  • Develop robust evaluation metrics, conduct experiments, and ensure the quality and reliability of our AI systems.
  • Contribute to building a best-in-class ML pipeline, from data preprocessing to model monitoring and iterative improvement.

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🙌 Requirements
  • Strong background in machine learning, with a focus on NLP, LLMs, or large-scale data processing.
  • Proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
  • Demonstrated track record in taking ML models from research to production.
  • Deep understanding of unsupervised learning techniques, statistical modeling, and deep learning architectures.
  • Curiosity, adaptability, and eagerness to tackle hard technical problems in a fast-paced startup environment.

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💡 Nice to Have
  • Experience with GCP, Kubernetes, or other cloud-based ML infrastructure.
  • Previous work on AI-driven customer feedback or conversational AI products.
  • Familiarity with techniques to accelerate LLM training and inference.
  • Contributions to open-source ML projects or research publications in top conferences/journals.

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💙 Benefits
  • Generous equity packages - your work drives our success, and you share in it.
  • Competitive salary with comprehensive health, dental, and vision coverage.
  • Flexible time off and paid company holidays.

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👣 Our Hiring Process
  1. Application & Review
  2. Introductory Chat (30 min)
  3. Technical Interview (45 min)
  4. Coding/ML Exercise (2 hrs)
  5. Team Meeting (In-person, Seattle Preferred)
  6. Offer & Celebration 🎉

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We embrace diverse backgrounds and unique perspectives. If you need accommodations during the interview process, let us know.