HubSpot's AI Platform Group is seeking a Principal Machine Learning Engineer to own AI Context. You will define the technical direction for applied ML and AI systems that transform complex data into customer value across the CRM platform. You will work across product, engineering, data, and ML teams to take ambiguous 0-to-1 opportunities from model development through evaluation, productionization, experimentation, and measurable business impact. Responsibilities include providing strategic direction and architectural leadership for major ML/AI projects across multiple teams, staying hands-on in technical design, model development, production systems, and code, and mentoring engineers to grow through complex technical projects. You will develop solutions to ambiguous problems that significantly impact customer experience, product strategy, or business goals, and design architectures for a variety of ML and AI Context problems—from business requirements to deployment. You will evaluate a wide range of ML techniques (deep learning, transformers, NLP, embeddings, retrieval, ranking, personalization) and tools (scikit-learn, PyTorch, TensorFlow), and implement reliable, scalable data processing, feature generation, context retrieval, model training, inference, monitoring, and feedback loops. Additional focus areas include privacy, bias, security, reliability, cost, maintainability, model quality, and data governance across the ML lifecycle. Collaboration with product, engineering, and data teams is essential. If you are passionate about applying machine learning and AI to trans

HubSpot's AI Platform Group is seeking a Principal Machine Learning Engineer to own AI Context. You will define the technical direction for applied ML and AI systems that transform complex data into customer value across the CRM platform. You will work across product, engineering, data, and ML teams to take ambiguous 0-to-1 opportunities from model development through evaluation, productionization, experimentation, and measurable business impact. Responsibilities include providing strategic direction and architectural leadership for major ML/AI projects across multiple teams, staying hands-on in technical design, model development, production systems, and code, and mentoring engineers to grow through complex technical projects. You will develop solutions to ambiguous problems that significantly impact customer experience, product strategy, or business goals, and design architectures for a variety of ML and AI Context problems—from business requirements to deployment. You will evaluate a wide range of ML techniques (deep learning, transformers, NLP, embeddings, retrieval, ranking, personalization) and tools (scikit-learn, PyTorch, TensorFlow), and implement reliable, scalable data processing, feature generation, context retrieval, model training, inference, monitoring, and feedback loops. Additional focus areas include privacy, bias, security, reliability, cost, maintainability, model quality, and data governance across the ML lifecycle. Collaboration with product, engineering, and data teams is essential. If you are passionate about applying machine learning and AI to trans