Machine Learning Scientist
Dublin, Ireland
Intercom
Intercom is the complete AI-first customer service solution, giving exceptional experiences for support teams with AI agent, AI copilot, tickets, phone & moreIntercom 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? 🚀
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Identify areas where ML can create value for our customers
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Identify the right ML framing of product problems
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Working with teammates and Product and Design stakeholders
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Conduct exploratory data analysis and research
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Deeply understand the problem area
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Research and identify the right algorithms and tools
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Being pragmatic, but innovating right to the cutting-edge when needed
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Perform offline evaluation to gather evidence an algorithm will work
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Work with engineers to bring prototypes to production
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Plan, measure & socialize learnings to inform iteration
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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! :)
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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
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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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Classification Clustering Data analysis EDA Engineering LLMs Machine Learning ML models NLP PhD Postdoc Research Statistics Testing
Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Flex vacation Gear Health care Home office stipend Insurance Parental leave Salary bonus Snacks / Drinks Startup environment
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