About the job
At Intercom, we are revolutionizing customer service through innovative AI solutions, striving to empower businesses to deliver exceptional customer experiences.
Our flagship AI agent, Fin, is the most advanced customer service AI available, enabling businesses to provide round-the-clock, flawless service and significantly enhance customer interactions. Fin seamlessly integrates with our Helpdesk, creating an all-encompassing solution known as the Intercom Customer Service Suite, designed to tackle complex queries that necessitate human intervention.
Founded in 2011 and trusted by nearly 30,000 businesses worldwide, Intercom is setting a new benchmark for customer service. Our core values drive us to push boundaries, operate with speed, and deliver unparalleled value to our clients.
We believe in the importance of speed, and Berlin epitomizes this with its unique combination of technical expertise and vibrant creative culture. It is a globally connected city, closely situated to our R&D hubs in Dublin and London, making it the ideal environment for top-tier technical talent to flourish and collaborate on ambitious projects.
This year, we aim to expand our Berlin team by hiring 100 professionals in engineering, AI, data science, product, and design. Joining us now means becoming part of the foundational R&D team in this region, allowing you to leave a lasting impact as we develop the world's leading customer agent!
What’s the opportunity?
We are seeking Senior Product Engineers to join our AI Group, focusing on the development of Intercom’s AI-driven products. As a Product Engineer in machine learning, you will collaborate closely with our ML Scientists and product teams, gaining a deep understanding of our products, customer needs, and our ML tech stack.
Your role will involve defining innovative ML features, researching suitable algorithms, and rapidly deploying prototypes to our customers. Our team is highly product-focused, working in partnership with Product and Design teams to expedite our production processes. Thanks to our dedicated engineering team, we frequently transition from successful offline tests to production within weeks.
We are passionate about leveraging machine learning technology, having productized everything from classic supervised models to groundbreaking unsupervised clustering algorithms and transformative applications of transformer neural networks. We rigorously test and measure the real customer impact of every model we implement.

