Staff Machine Learning Backend Engineer
It is the only complete customer service solution that provides a seamless customer experience across automation and human support. Customer service teams from more than 25,000 global organizations, including Atlassian, Amazon and Microsoft, use Intercom to send over 600 million messages per month and enable interactions with over 800 million monthly active end users. The company was founded in 2011 and is backed by leading venture capitalist including Bessemer Venture Partners, Kleiner Perkins and Social Capital. We live by our six company values everyday: Success First, Customer Obsessed, Incredibly High Standards, Open Mindedness, Resilience, Impatience, and Positive & Optimistic. They are stitched into the way we work, interact with others, and hold ourselves accountable. We’re eager to hire individuals who are passionate about our mission, deeply aligned with our values, and are excited to help shape the future of customer service.
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
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
- ML Ops experience
- GPU, Pytorch, OS internals
- Deep knowledge of AWS services
- Track record shipping ML products
- Large scale ETL
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
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
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.
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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