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?
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Identify areas where ML can create value for our customers
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Contribute to finding the right ML framing of a product problem
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Working with teammates and Product and Design stakeholders
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Taking algorithms which work offline, and putting them in a production setting
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Deeply understand and modify as needed
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Solve hard scalability and optimization problems
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Run production ML infrastructure, evolve it over time
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Build new data infrastructure to enable exploration
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Establish processes for large scale data analyses, model development, validation, and implementation
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Work with teammates to measure and iterate on algorithm performance
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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.
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Excellent pragmatic engineering skills
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Familiar with tools used to write, test, deploy, debug and monitor software
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Comfort owning features from inception to outcome.
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7+ years experience in a production environment, with contributions to the design and architecture of distributed systems.
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We’re looking for engineers who can confidently put ML-powered features in production.
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Strong communication skills, both within engineering teams and across disciplines.
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Excellent programming skills
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Comfort with ambiguity
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BSc in Computer Science, or similar knowledge
Bonus skills & attributes
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Deep knowledge of AWS services
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ML Ops experience
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Large scale computation experience
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Track record shipping ML products
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Experience in a research environment
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Algorithmic optimisation experience
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Advanced education in CS, ML, Math, Stats, or similar
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Practical stats knowledge (experiment design, dealing with confounding, etc)
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Experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
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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! :)
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Competitive salary and equity in a fast-growing start-up
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We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
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Regular compensation reviews - we reward great work!
- Pension scheme & match up to 4%
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Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
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Flexible paid time off policy
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Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
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If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
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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
