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 backend engineers collaborate with scientists to deeply understand research context, and 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 deplo

If you excel in scaling backend systems but have a bit less hands-on experience with ML systems (which you happily make up for with your keen interest), we'd love to hear from you! 🌟

What will I be doing? 🚀

  • Taking algorithms which work offline, and putting them in a production setting
    • Deeply understand and modify as needed
  • Solve hard scalability and optimization problems
  • Improving our dev tooling
  • Run production ML infrastructure, and evolving it over time
  • Build new data infrastructure to enable exploration
  • Establish processes for large scale data analyses, model development, validation and implementation
  • Work with teammates to measure and iterate on algorithm performance
  • 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.

  • Excellent pragmatic engineering skills
    • Familiar with tools used to write, test, deploy, debug and monitor software
    • Comfort owning features from inception to outcome.
  • 7+ years experience in a production environment, with contributions to the design and architecture of distributed systems.
  • Strong communication skills, both within engineering teams and across disciplines.
  • Excellent programming skills
  • Comfort with ambiguity
  • BSc in Computer Science, or similar knowledge

Bonus skills & attributes 🙌

  • ML Ops experience
  • GPU, Pytorch, OS internals
  • Deep knowledge of AWS services
  • Track record shipping ML products
  • Large scale ETL

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
  • Regular compensation reviews - we reward great work
  • 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, to let you spend valuable time with your loved ones
  • MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

Note:

We’ve put together descriptions for both Scientist and Engineer archetypes of this role.

In practice, we’re interested in excellent candidates right across this spectrum.

 

#LI-Hybrid

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.

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