Staff Machine Learning Scientist

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.

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 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.

What will I be doing?

Play an active role in hiring, mentoring and career development of other engineers

Raise the bar for technical standards, performance, reliability, and operational excellence

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

What skills might I need?

5-8 years applied ML experience

Previous background in a senior/staff role (data science, software development or academic)

Significant, demonstrated impact that your work has had on the product and/or the teams

Strong programming skills

Experience as the primary technical leader for a team

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

Bonus skills & attributes

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.