Sr. Machine Learning Engineer I
HubSpot · Remote (United States) · Engineering
About this role
HubSpot is hiring a senior-level Machine Learning Engineer as a remote position. The posting calls out experience with Python, PyTorch, LLMs, Prompt Engineering. Compensation is listed at $165,500–$248,300 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Remote (United States)
- Work mode
- Remote
- Department
- Engineering
More roles at HubSpot
Job description
from HubSpot careersPOS-23565
About the Role
HubSpot's Agent Platform team is building Breeze Studio, our custom agent creation product that lets customers define, deploy, and improve AI agents that work on their behalf inside HubSpot. As a Machine Learning Engineer on the Agent Orchestration ML team, you'll own the models and systems that determine whether those agents are any good.
This is core ML work: prompt optimization, LLM evaluation, model fine-tuning, and inference infrastructure. You'll work directly with LLM vendors like OpenAI, run model performance experiments, and ship improvements that customers notice. The team is small (currently 2 MLEs), the surface area is large, and the scope is yours to define.
Custom agents are central to HubSpot's strategic direction as an AI-first CRM. This is not a supporting role.
What You'll Do
- Design and run experiments to improve agent quality: better tool use, better reasoning, better outputs, using frameworks like DSPy and VLLM
- Build and maintain evaluation infrastructure to measure what's working and catch regressions before customers do
- Optimize LLM inference: latency, cost, model routing, and quality tradeoffs
- Partner with product teams on model selection and performance benchmarking
- Work closely with product engineers and PMs to translate customer quality problems into ML hypotheses and solutions