Senior Machine Learning Scientist · Intercom

Sat, 25 Apr 2026 20:57:48 GMT
Engineering

Intercom · London, England · hybrid

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

We are looking for a Senior Machine Learning Scientist to join our Machine Learning team. This team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers' hands. We are an extremely product-focused team, working in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

As a Senior Machine Learning Scientist, you will identify areas where ML can create value for our customers, work with teammates and Product and Design stakeholders, conduct exploratory data analysis and research, deeply understand the problem area, research and identify the right algorithms and tools, perform offline evaluation to gather evidence an algorithm will work, work with engineers to bring prototypes to production, plan, measure & socialize learnings to inform iteration, and partner deeply with the rest of team, and others, to build excellent ML products.

We are looking for someone with broad applied machine learning knowledge, 3-5 years applied ML experience, practical stats knowledge (experiment design, dealing with confounding etc), intermediate programming skills, strong communication skills, both within engineering teams and across disciplines, comfort with ambiguity, typically have advanced education in ML or related field (e.g. MSc), and scientific thinking skills. Bonus skills and attributes include a track record shipping ML products, PhD or other experience in a research environment, deep experience in an applicable ML area. e.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering, strong stats or math background, visualization, data skills, SQL, matplotlib, etc.