HubSpot’s mission is to help millions of companies Grow Better. We believe machine learning (ML) and AI will allow our Go-to-Market (GTM) teams to more effectively serve even more companies. We’re seeking a talented, experienced Senior ML Engineer to join our Data, Systems & Intelligence (DSI) team to support internal Sales and Customer Success (CS) clients through the delivery of scalable AI/ML and other data products to improve the efficiency and efficacy of frontline Sales and Customer Success reps and solve for their pain points.
You will be joining a high-growth, high-powered team of Data Scientists, ML Engineers, and Analytic Engineers that deeply values intellectual curiosity, collaboration, and autonomy. You will have an enormous impact in a rapidly growing space–we’ve got big plans and want talented, passionate engineers to help us achieve them. In addition to working within the team, you will embed with our Flywheel Product team of Backend Engineers building ML/AI-driven solutions for CS reps. HubSpot is early in its internal ML/AI maturity curve, which provides a unique opportunity for big impact.
Objectives of this Role
- Build, train, evaluate, and deploy ML models and generative AI (GAI) solutions at scale
- Work with complex datasets (both structured and unstructured) to extract relevant features and insights
- Conduct experiments and evaluations of ML and generative AI models, using statistical methods and visualization tools to assess performance and identify areas for improvement
- Train and fine-tune LLMs for specific, tailored use cases
- Build strong relationships with internal stakeholders and develop a deep understanding of their business problems
- Keep current with the research and trends in AI/ML/GAI, and contribute to the development of new algorithms and techniques
- Participate in code reviews, testing, and documentation activities, ensuring high quality and maintainability of the codebase
- Mentor other junior ML Engineers and Data Scientists to improve their coding proficiency, algorithmic efficiency and general knowledge of the rapidly evolving field
About you:
- Degree in computer science, statistics, applied mathematics, economics, or other quantitative discipline
- 3+ years experience in machine learning with multiple models deployed in operational settings
- Expert knowledge of a breadth of machine learning/AI techniques and a thorough understanding of the best approach to use for a given situation
- Strong familiarity of Python programming and ML frameworks (Scikit-learn, TensorFlow, PyTorch, HuggingFace, etc.)
- Familiarity with CI/CD systems (e.g. GitHub Actions, Jenkins, CircleCI, etc.)
- Familiarity with monitoring & alerting systems (DataDog, Monte Carlo, Cloudwatch)
- Familiarity with Snowflake, SQL, as well as DBT and jinja templating
- Familiarity with standard ML deployment stack (Docker, Kubernetes, Spark, dask, etc.)
- Ability to own a software project from planning to maintenance. Agile or scrum familiarity preferred. Works well with backend/frontend/full stack engineers.
- Able to clearly communicate technical concepts to business leaders
- Creative, collaborative problem solver with experience delivering iterative solutions to difficult problems
Bonus points:
- MS or PhD in a quantitative field
- Familiarity with Java
- Experience working with Kafka or other streaming data
- Prior academic or industrial experience with LLMs or RAG flows
- Prior experience supporting GTM teams or functions, especially in B2B SaaS companies
- Familiarity with vector databases
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