Principal Machine Learning Engineer

About the Role HubSpot's AI Platform Group delivers ML and AI foundations to enable product teams across the company to create easy, accurate, and consistent AI features. This Principal Machine Learning Engineer role focuses on AI Context: building systems that help HubSpot's AI understand customer, company, activity, and workflow data across the CRM platform. You will define the technical direction for applied ML and AI systems and work across product, engineering, data, and ML teams to move ambiguous opportunities from 0 to 1 through model development, evaluation, productionization, experimentation, and measurable customer or business impact. What You'll Do

• Provide strategic direction and architectural leadership for major ML/AI projects across multiple teams, systems, or product surfaces.
• Regularly mentor, coach, and teach engineers, including helping senior ICs grow through complex technical projects.
• Stay hands-on in technical design, model development, production systems, and code while leading by example through collaboration with cross-functional stakeholders.
• Design and implement reliable, scalable systems for data processing, feature generation, context retrieval, model training, inference, experimentation, monitoring, and feedback loops.
• Evaluate ML solutions considering privacy, bias, security, reliability, cost, maintainability, model quality, and data governance across the lifecycle.
• Collaborate with product, data, and engineering teams to translate business requirements into effective ML solutions, including applied AI, retrieval, and recommendations. What We're Looking For
• Long track record of delivering high-value, cross-team and cross-product projects.
• Senior individual contributor with hands-on experience in model development, production systems, and technical leadership.
• Expert understanding of ML techniques: deep learning, transformers, LLMs, retrieval, ranking, recommendations, classification, NLP, personalization; proficient with frameworks like scikit-learn, PyTorch, TensorFlow.
• Ability to craft the right architecture for ML/AI context problems and guide teams beyond the status quo.
• Experience turning messy, incomplete, or heterogeneous data into useful AI context for customer-facing products (e.g., CRM, activity, workflow data).
• Strong communication, mentoring, and collaboration across product, engineering, data, and ML teams.
• Comfortable evaluating across metrics and governance concerns, including privacy, bias, security, and data governance. Nice to Have
• Experience with Applied and Predictive AI, especially recommendation systems, embeddings, semantic retrieval, and related evaluation.
• Prior work in CRM or business-to-customer contexts and building scalable ML platforms. Compensation & Benefits
• Annual Cash Compensation Range: $285,800—$457,300 USD, with potential on-target commissions, annual bonuses, and eligibility for equity (RSUs).
• Benefits and perks vary, with details provided by HubSpot's compensation philosophy and benefits program.