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
- Identify the right ML framing of product problems
- Working with teammates and Product and Design stakeholders
- Conduct exploratory data analysis and research
- Deeply understand the problem area
- Research and identify the right algorithms and tools
- Being pragmatic, but innovating right to the cutting-edge when needed
- Perform offline evaluation to gather evidence an algorithm will work
- Work with engineers to bring prototypes to production
- Plan, measure & socialize learnings to inform iteration
- Partner deeply with the rest of team, and others, to build excellent ML products
What skills might I need?
- 1-3 years of ML experience. Ideally, in a fast-moving environment (like Intercom), but it's also fine if you worked on interesting and complex problems in research (e.g. as a postdoc or a research assistant, or even in your PhD)
- Intermediate programming skills. You should be comfortable with writing code (mostly) autonomously, considering edge cases and knowing how to test your work
- Solid theoretical foundation in stats and ML.We don't expect you to know how an LLM like Mistral works at low level (although it's great if you do know it), but you should be well-familiar with things like classification and regression, as well as testing of statistical hypotheses and evaluation of ML models
- Scientific mindset.You're naturally critical and rely on data and evidence when making judgements. You're ready to abandon ideas that turned out to be bad, even if they were your own
- Strong communication skills.You mostly will be communicating to members of engineering teams, but occasionally you'll also have to explain something to a less technical person
Bonus skills & attributes
- Advanced education in ML or related field (e.g. PhD or MSc)
- Deep experience in NLP or LLMs
- Strong visualisation and data wrangling skills
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
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