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Staff Machine Learning Engineer

Intercom
Full-time
On-site
Dublin, Ireland

Intercom was founded in 2011 to change the standard of customer service online. Our AI-first customer service platform is a totally new way to deliver customer service and is designed to transform the way businesses interact with their customers through AI. We all know that customer service on the internet sucks. It’s slow and impersonal. We help businesses provide instant and exceptional service to their customers and maximize their support agents’ productivity, efficiency, and performance—all through our single AI system. More than 25,000 businesses use Intercom to send millions of messages to millions of customers each month.Intercom has been a long-standing product leader and cultural icon in the technology and startup worlds for more than a decade. We set the pace for our industry and live by our values that allow us to push boundaries, build with speed and intensity, and deliver incredible value to our customers.Join us on our mission to redefine customer service and make internet business personal.


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? 




  • Identify areas where ML can create value for our customers




  • Contribute to finding the right ML framing of a product problem 




  • Working with teammates and Product and Design stakeholders




  • Taking algorithms which work offline, and putting them in a production setting




  • Deeply understand and modify as needed




  • Solve hard scalability and optimization problems




  • Run production ML infrastructure, evolve 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.




  • We’re looking for engineers who can confidently put ML-powered features in production.




  • 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 




  • Deep knowledge of AWS services




  • ML Ops experience




  • Large scale computation experience




  • Track record shipping ML products




  • Experience in a research environment




  • Algorithmic optimisation experience




  • Advanced education in CS, ML, Math, Stats, or similar




  • Practical stats knowledge (experiment design, dealing with confounding, etc)




  • Experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering




  • 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! :)




  • 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!



  • Pension scheme & match up to 4%


  • Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents




  • Flexible paid time off policy




  • Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones




  • 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



  • Relocation support for those moving to our offices


#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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