Principal Machine Learning Engineer

DataJobs; Cambridge (MA); Presencial; USD 286.000 - 457.000; Jornada completa

Descripción de la vacante

HubSpot is seeking a Principal Machine Learning Engineer to build foundational AI infrastructure for agentive product experiences in Cambridge, MA. The role focuses on scaling systems for evaluation, quality signals, and cost efficiency across HubSpot’s AI-powered platforms.

You will lead platform engineering for agent runtime, evaluation, and model optimization, collaborating with infrastructure, product, backend, and ML teams to advance production-ready capabilities across the company.

Formación

• Must have deep experience with production machine learning, LLMs, or AI infrastructure.
• Experience building scalable systems where reliability, latency, quality, and cost are key constraints.
• Platform-oriented mindset focused on durable systems rather than one-off solutions.
• Ability to collaborate across infrastructure, product, backend, and ML teams.

Responsabilidades

• Build infrastructure for agent runtime, evaluation, quality measurement, and model optimization.
• Create tooling to understand evaluation performance, coverage gaps, and readiness of user questions.
• Design signal pipelines to surface user frustration, agent failure states, and quality issues before CSAT drops.
• Help define a HubSpot-specific AI benchmark for evaluating model performance on HubSpot workloads.
• Build systems to evaluate new models across agents, improving product quality and reducing cost.
• Make fine-tuning and task-specific optimization more repeatable for HubSpot’s AI use cases.

Conocimientos

Production ML

LLMs

AI infrastructure

Scalability

Reliability

Cost optimization

Cross-functional collaboration

Evaluation frameworks

Model serving

Fine-tuning

Descripción del empleo

The Principal Machine Learning Engineer role at HubSpot focuses on building foundational AI infrastructure for agentic product experiences. You will help design and scale systems that improve evaluation, quality, and cost efficiency across HubSpot’s agent platforms.

Role Focus

In this position, you will work on high-scope platform engineering for agent runtime, evaluation, quality measurement, and model optimization. The work supports Breeze Engine and Aviator, with an emphasis on strengthening how models are evaluated and routed, and how quality signals are produced and used to drive product improvements across the company.

Responsibilities

• Build infrastructure for agent runtime, evaluation, quality measurement, and model optimization.
• Create tooling that enables teams to understand where their evaluations perform well, where coverage is missing, and which user questions are currently beyond the system’s readiness.
• Design signal pipelines to surface user frustration, agent failure states, and quality issues before they appear 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.

Requirements

• Deep experience with production machine learning, LLMs, or AI infrastructure.
• Experience building systems at scale where reliability, latency, quality, and cost are key constraints.
• A platform-oriented mindset focused on durable systems rather than one-off solutions.
• Ability to collaborate across infrastructure, product, backend, and ML teams.
• Experience in one or more areas such as evaluation frameworks, model serving, fine-tuning, signal extraction, experimentation, feedback loops, or model optimization.
• Interest in ambiguous, foundational problems where many answers still need to be developed.
• Technical credibility and clear judgment to influence senior engineers and leaders.

About the Team

HubSpot is building foundational AI infrastructure for its next generation of agentic product experiences. This team owns Breeze Engine, the platform behind Breeze Assistant and other AI-powered product experiences, and Aviator, HubSpot’s internal framework for building and running agents. This is a high-scope infrastructure role focused on creating leverage across the company.

Work Location

Cambridge, MA (onsite)

Compensation

USD 285,800 - 457,300 per year

Work Flexibility and In-Person Expectations

• If you join the Engineering team as a Remote employee or from the Office, you will be required to attend a regional HubSpot office for in-person onboarding.
• If you join the broader Product team, you will also attend in-person events, including your Product Group Summit and other gatherings.

Accommodations

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