Senior Machine Learning Engineer, null

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. 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-focused team that works in partnership with Product and Design functions. 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. What will I be doing?

1. Identify areas where ML can create value for our customers
2. Contribute to finding the right ML framing of a product problem
3. Work with teammates and Product and Design stakeholders
4. Take algorithms which work offline and put them in a production setting
5. Deeply understand and modify as needed
6. Solve hard scalability and optimization problems
7. Build new data infrastructure to enable exploration
8. Establish processes for large scale data analyses, model development, validation, and implementation
9. Work with teammates to measure and iterate on algorithm performance
10. Partner deeply with the rest of the team to build excellent ML products

What skills might I need?

1. Excellent pragmatic engineering skills
2. Familiar with tools used to write, test, deploy, debug and monitor software
3. Comfort owning features from inception to outcome
4. 5+ years experience in a production environment, with contributions to the design and architecture of distributed systems
5. Strong communication skills, both within engineering teams and across disciplines
6. Excellent programming skills
7. Comfort with ambiguity
8. BSc in Computer Science, or similar knowledge
9. Deep knowledge of AWS services
10. Track record shipping ML products
11. Experience in a research environment
12. Algorithmic optimisation experience
13. Advanced education in CS, ML, Math, Stats, or similar
14. Practical stats knowledge (experiment design, dealing with confounding, etc)
15. Experience in an applicable ML area (e.g., NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering)

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. Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents. Open vacation policy and flexible holidays so you can take time off when you need it. 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. 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. 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 any legally recognized protected basis under federal, state, or local law. #J-18808-Ljbffr