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, Intercom is bringing AI features to market before anyone else.
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?
1. Identify areas where ML can create value for our customers
2. Contribute to finding the right ML framing of a product problem
3. Working with teammates and Product and Design stakeholders
4. Taking algorithms which work offline, and putting them in a production setting
5. Deeply understand and modify as needed
6. Solve hard scalability and optimization problems
7. Run production ML infrastructure, evolve it over time
8. Build new data infrastructure to enable exploration
9. Establish processes for large scale data analyses, model development, validation, and implementation
10. Work with teammates to measure and iterate on algorithm performance
11. Partner deeply with the rest of team, and others, to build excellent ML products
What skills might I need?
These are meant to be indicative, not hard requirements.
12. Excellent pragmatic engineering skills
13. Familiar with tools used to write, test, deploy, debug and monitor software
14. Comfort owning features from inception to outcome.
15. 5+ years experience in a production environment, with contributions to the design and architecture of distributed systems.
16. We’re looking for engineers who can confidently put ML-powered features in production.
17. Strong communication skills, both within engineering teams and across disciplines.
18. Excellent programming skills
19. Comfort with ambiguity
20. BSc in Computer Science, or similar knowledge
Bonus skills & attributes
21. Deep knowledge of AWS services
22. ML Ops experience
23. Large scale computation experience
24. Track record shipping ML products
25. Experience in a research environment
26. Algorithmic optimisation experience
27. Advanced education in CS, ML, Math, Stats, or similar
28. Practical stats knowledge (experiment design, dealing with confounding, etc)
29. Experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
30. Visualization, data skills, SQL, matplotlib, etc.
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! :)
31. Competitive salary and equity in a fast-growing start-up
32. We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
33. Regular compensation reviews - we reward great work!
34. Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
35. Open vacation policy and flexible holidays so you can take time off when you need it
36. Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
37. If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
38. MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done
Policies
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 two days per week.
We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus 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. 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.