Job Description
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. 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 deploy. 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 the 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 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 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 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 #J-18808-Ljbffr