POS-33520

Principal Machine Learning Engineer

About the Team

HubSpot is building the foundational AI infrastructure that powers our next generation of agentic product experiences. We're looking for a Principal Machine Learning Engineer to help shape the base layer that product teams build on: agent runtime, evaluation systems, quality signals, model optimization, fine-tuning, and model routing.

This team owns Breeze Engine, the platform behind Breeze Assistant and other AI-powered product experiences, as well as Aviator, HubSpot's internal framework for building and running agents. This is not a feature-team role it is a high-scope infrastructure role focused on building systems that create leverage across the company.
What You'll Work On

• Build infrastructure for agent runtime, evaluation, quality measurement, and model optimization.
• Create tooling that helps teams understand where their evals are strong, where coverage is missing, and where users are asking questions the system is not yet prepared to handle.
• Design signal pipelines that surface user frustration, agent failure states, and quality issues before they show up as CSAT drops.
• Help define a HubSpot-specific AI benchmark for evaluating model performance on real HubSpot workloads.
• Build systems to evaluate new models across agents, improving product quality, reducing cost, and supporting future model routing.
• Make fine-tuning and task-specific optimization more repeatable for HubSpot's AI use cases.

What We're Looking For

We're looking for a senior technical leader who:

• Has deep experience with production ML, LLM, or AI infrastructure.
• Has built systems at scale where reliability, latency, quality, and cost matter.
• Thinks in platforms, not one-off solutions.
• Can work across infrastructure, product, backend, and ML teams.
• Has experience with areas like eval frameworks, model serving, fine-tuning, signal extraction, experimentation, feedback loops, or model optimization.
• Is excited by ambiguous, foundational problems where many of the answers still need to be invented.
• Can influence senior engineers and leaders through technical credibility and clear judgment.

Why This Role Matters

This is a chance to help define how AI infrastructure works across HubSpot. The person in this role will help set the technical direction for how we evaluate, improve, and scale AI agents across the company.

Pay & Benefits

The cash compensation below includes base salary, on-target commission for employees in eligible roles, and annual bonus targets under HubSpot's bonus plan for eligible roles. In addition to cash compensation, some roles are eligible to participate in HubSpot's equity plan to receive restricted stock units (RSUs). Some roles may also be eligible for overtime pay. Individual compensation packages are tailored to your skills, experience, qualifications, and other job-related reasons.

This resource will help guide how we recommend thinking about the range you see. Learn more about HubSpot's compensation philosophy.

Benefits are also an important piece of your total compensation package. Explore the benefits and perks HubSpot offers to help employees grow better.

At HubSpot, fair compensation practices aren't just about checking off the box for legal compliance. It's about living out our value of transparency with our employees, candidates, and community.

Annual Cash Compensation Range:

$285,800-$457,300 USD

At HubSpot, we value both flexibility and connection. Whether you're a Remote employee or work from the Office, we want you to start your journey here by building strong connections with your team and peers. If you are joining our Engineering team, you will be required to attend a regional HubSpot office for in-person onboarding. If you join our broader Product team, you'll also attend other in-person events, such as your Product Group Summit and other gatherings, to continue building on those connections.

If you require an accommodation due to travel limitations or other reasons, please inform your recruiter during the hiring process. We are committed to supporting candidates who may need alternative arrangements