Machine Learning Engineer • Senior

Who you are

You have a strong background in machine learning engineering, with experience in building and deploying ML systems that drive real-world impact. Your expertise includes working with large language models (LLMs) and classical machine learning techniques, allowing you to create scalable solutions that meet business needs. You are comfortable collaborating with cross-functional teams, including Sales and Customer Success, to translate complex business questions into actionable ML solutions.

You possess a solid understanding of LLM evaluation techniques, including offline evaluations and automated metrics, ensuring the quality and relevance of the models you develop. Your experience in building and maintaining LLM infrastructure, such as vector stores and embedding pipelines, sets you apart as a candidate who can handle the end-to-end lifecycle of machine learning systems.

What you'll do

In this role, you will design, build, and deploy machine learning systems that support HubSpot's go-to-market strategies. You will partner closely with Sales and Customer Success leaders to develop ML-powered solutions that drive measurable outcomes. Your responsibilities will include applying LLM evaluation techniques to ensure the quality and safety of the models you create, as well as collaborating with Data Scientists to productionize models and experiments into robust systems.

You will own the end-to-end lifecycle for both classical ML and LLM-based systems, managing prompt strategies and retrieval methods to optimize performance. Your work will directly influence forecasting and prioritization across teams, making your contributions vital to HubSpot's mission of helping organizations grow better.

What we offer

HubSpot provides a collaborative and innovative work environment where your contributions will have a significant impact. You will have the opportunity to work with cutting-edge technologies and be part of a team that values creativity and problem-solving. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse teams build better products.