Machine Learning Scientist

Qualifications

• Minimum Qualifications 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
• 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

Benefits

• 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

Responsibilities

• 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
• 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
• 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

Full Description

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. 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. 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. Minimum Qualifications 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. 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. 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. Application & Review Introductory Chat (30 min) Technical Interview (45 min) Team Meeting (In-person, Seattle Preferred) We embrace diverse backgrounds and unique perspectives. If you need accommodations during the interview process, let us know. Empower Users Build Better Products Faster #J-18808-Ljbffr