Staff Machine Learning Engineer
Intercom
This job is no longer accepting applications
See open jobs at Intercom.See open jobs similar to "Staff Machine Learning Engineer" Freestyle Capital.Intercom is an AI powered, automation-first customer service platform that lets businesses deliver fast support, keeping customers satisfied, costs low, and service teams happy.
It is the only complete customer service solution that provides a seamless customer experience across automation and human support. Customer service teams from more than 25,000 global organizations, including Atlassian, Amazon and Microsoft, use Intercom to send over 600 million messages per month and enable interactions with over 800 million monthly active end users. The company was founded in 2011 and is backed by leading venture capitalist including Bessemer Venture Partners, Kleiner Perkins and Social Capital. We live by our six company values everyday: Success First, Customer Obsessed, Incredibly High Standards, Open Mindedness, Resilience, Impatience, and Positive & Optimistic. They are stitched into the way we work, interact with others, and hold ourselves accountable. We’re eager to hire individuals who are passionate about our mission, deeply aligned with our values, and are excited to help shape the future of customer service.
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!
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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
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organisation. We're committed to an inclusive and diverse Intercom! We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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.
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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This job is no longer accepting applications
See open jobs at Intercom.See open jobs similar to "Staff Machine Learning Engineer" Freestyle Capital.