Senior Machine Learning Engineer
Dublin, Ireland
Intercom
Faster resolutions, higher CSAT, and lighter support volumes with the only platform to combine the power of automation and human customer support.Intercom is an AI-first customer service platform that helps businesses deliver better, faster, more personalized support.
Intercom is bringing AI-first Customer Service to the world, dramatically improving experiences for customers, support agents, and managers alike.Modern, fast, and easy-to-use, Intercom’s complete AI-first Customer Service Platform enhances the customer experience, improves operational efficiency, and scales with our customers’ business every step of the way. Intercom is also the most innovative and fastest improving product on the market. Shipping over 200 product improvements every year, Intercom is bringing AI features to market before anyone else.
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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5+ 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!
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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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Open vacation policy and flexible holidays so you can take time off when you need it
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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.
Is this role not quite what you're looking for? Join our Talent Community to stay connected with us.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Bayesian Clustering Computer Science CX Deep Learning Distributed Systems Engineering Machine Learning Mathematics Matplotlib ML infrastructure ML models NLP Reinforcement Learning Research SQL
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Gear Health care Insurance Parental leave Salary bonus Snacks / Drinks Startup environment
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