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 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
Work with teammates and Product and Design stakeholders
Take algorithms which work offline, and put 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 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 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
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