Senior Machine Learning Scientist

Senior Machine Learning Scientist (London)

London, England

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.

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.

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 an extremely product focussed team. We work 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.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting‑edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

• Identify areas where ML can create value for our customers
• Identify the right ML framing of product problems
• Working 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
• Being 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 team, and others, to build excellent ML products

• 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

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

Mac Books 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.

We have a radically open and accepting culture  avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not…