Principal Machine Learning Engineer
Core
Building systems that help HubSpot's AI understand customer, company, activity, and workflow data across the CRM platform to transform complex data into customer value.
Role type
Principal Machine Learning Engineer (Applied AI)
Builds
AI context systems for CRM, including data processing, feature generation, context retrieval, model training, inference, and experimentation pipelines.
Domain
SaaS / Customer Relationship Management (CRM) / Applied Machine Learning
Deliverable
production ML models
Required skills
Deep learning, optimization, regression, transformers, large language models, transfer learning, retrieval, ranking, recommendations, classification, NLP, personalization, scikit-learn, PyTorch, TensorFlow, model-serving, data governance, privacy, bias mitigation, semantic retrieval, embeddings, entity understanding, experimentation design, heterogeneous data integration.
Preferred skills
Architectural leadership for major ML/AI projects, mentoring senior ICs, pragmatic decision-making on ML vs. rules vs. product changes, guiding teams beyond status quo.
Technologies
PyTorch, TensorFlow, scikit-learn, modern model-serving systems, LLM frameworks.
Responsibilities
Define technical direction for applied ML and AI systems; develop, evaluate, and productionize models for ambiguous 0-to-1 opportunities; mentor and coach engineers on complex technical projects; evaluate privacy, bias, security, reliability, and cost across the ML lifecycle; build scalable systems for data processing and inference.
Seniority
Principal, hands-on IC with strategic leadership