2 months ago
Dublin, IrelandSenior
Responsibilities
- Identify customer opportunities where machine learning can create value and frame product problems appropriately.
- Conduct exploratory data analysis, research algorithms and tools, and develop practical prototypes.
- Perform offline evaluations to determine whether algorithms are likely to work.
- Collaborate with engineers to bring ML prototypes into production.
- Plan, measure, and communicate learnings to support product iteration.
- Partner with Product, Design, engineering, and other stakeholders to build ML products.
Requirements
- Broad applied machine learning knowledge and 3–5 years of applied ML experience.
- Practical statistics knowledge, including experiment design and handling confounding factors.
- Intermediate programming skills and strong communication across engineering and other disciplines.
- Comfort with ambiguity and strong scientific thinking skills.
- Typically advanced education in machine learning or a related field, such as an MSc.
- Preferred qualifications include a track record of shipping ML products, research-environment experience or a PhD, and expertise in NLP, deep learning, Bayesian methods, reinforcement learning, clustering, statistics, mathematics, visualization, data, SQL, or matplotlib.
Benefits
- Benefits and programs support health and wellbeing, family, time away from work, and financial future, with offerings varying by location.
- Hybrid working policy with at least three days per week in the office and flexibility to work from home.
- Equal Employment Opportunity and a diversity-focused workplace.
Tech Stack
MatplotlibSQL
Categories
About Intercom
Intercom builds a customer service platform that combines an AI agent (Fin), live chat, and a modern help desk to support sales and support teams. It sells its software as a SaaS subscription to businesses that want to manage customer conversations across web, mobile, and email with automation and analytics. Founded in 2011 and headquartered in San Francisco, the company is privately held and serves startups through large enterprises.