Overview

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 transform their customer experiences for the better. Fin can be combined with our Helpdesk to become the Intercom Customer Service Suite, providing AI-enhanced support for more complex or high-touch queries that require a human agent. Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

What’s the opportunity?

Intercom’s Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are a product-focused team that works in partnership with Product and Design functions. Our dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We apply machine learning technology across a range of models and product areas, testing and measuring real customer impact of each deployment.

What will I be doing?

• Identify areas where ML can create value for our customers
• Identify the right ML framing of product problems
• 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
• Be pragmatic, but innovating right to the cutting-edge when needed
• 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
• Partner deeply with the rest of the team, and others, to build excellent ML products

What skills might I need?

• Broad applied machine learning knowledge
• 3-5 years applied ML experience
• Practical stats knowledge (experiment design, dealing with confounding etc)
• 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)
• Scientific thinking skills
• 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

Benefits

• We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!
• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Pension scheme & match up to 4%
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done
• Relocation support for those moving to our offices
• Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

Working culture & Equal Opportunity

Intercom has a radically open and accepting culture. We value diversity and are committed to Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.