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Intercom is an AI-first customer service platform that helps businesses deliver better, faster, more personalized support.
Intercom is bringing AI-first Customer Service to the world, dramatically improving experiences for customers, support agents, and managers alike. Modern, fast, and easy-to-use, Intercom’s complete AI-first Customer Service Platform enhances the customer experience, improves operational efficiency, and scales with our customers’ business every step of the way. Intercom is also the most innovative and fastest improving product on the market, shipping over 200 product improvements every year.
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-focused team, working in partnership with Product and Design functions. 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, productizing everything from classic supervised models to cutting-edge unsupervised clustering algorithms and novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.
What will I be doing?
1. Play an active role in hiring, mentoring, and career development of other engineers.
2. Raise the bar for technical standards, performance, reliability, and operational excellence.
3. Identify areas where ML can create value for our customers.
4. Identify the right ML framing of product problems - working with teammates and Product and Design stakeholders.
5. Conduct exploratory data analysis and research - deeply understand the problem area.
6. Research and identify the right algorithms and tools - being pragmatic, but innovating right to the cutting-edge when needed.
7. Perform offline evaluation to gather evidence an algorithm will work.
8. Work with engineers to bring prototypes to production.
9. Plan, measure & socialize learnings to inform iteration.
10. Partner deeply with the rest of the team and others to build excellent ML products.
What skills might I need?
1. 5-8 years applied ML experience.
2. Previous background in a senior/staff role (data science, software development, or academic).
3. Significant, demonstrated impact that your work has had on the product and/or the teams.
4. Experience as the primary technical leader for a team.
5. Strong communication skills, both within engineering teams and across disciplines.
6. Comfort with ambiguity.
7. Typically have advanced education in ML or related field (e.g., MSc).
8. Scientific thinking skills.
9. Track record shipping ML products.
10. PhD or other experience in a research environment.
11. Deep experience in an applicable ML area - e.g., NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering.
12. Strong stats or math background.
We are a well-treated bunch, with awesome benefits! Competitive salary and equity in a fast-growing start-up, lunch every weekday, a variety of snacks, and a fully stocked kitchen. Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents. Open vacation policy and flexible holidays so you can take time off when you need it. Paid maternity leave, as well as 6 weeks paternity leave for fathers. 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. Intercom has a hybrid working policy, expecting employees to be in the office at least two days per week.
We have a radically open and accepting culture at Intercom, focusing on doing incredible work to achieve our goals and unite the company through our core values. Intercom values diversity and is committed to a policy of Equal Employment Opportunity, ensuring no discrimination against applicants or employees on any legally recognized protected basis.
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