Foursquare is the leading independent location technology platform, powering business solutions and consumer products through a deep understanding of location. Foursquare’s business solutions include Pilgrim SDK, Places API, Analytics, Placed powered by Foursquare, and Pinpoint. Together, these products empower brands to analyze trends; measure foot traffic lift; optimize advertising campaigns; and drive deeper engagement via Foursquare’s industry-leading developer tools, which have been selected by 150,000 developers including AccuWeather, Apple, Samsung, Microsoft, Snapchat, Tinder, TripAdvisor, Twitter, and Uber. Our toolkit also includes our consumer apps Foursquare City Guide and Swarm. Over the past 10 years, we’ve counted more 13 billion verified signals from people around the world, helping us to keep our dynamic map and models fresh and up-to-date.
About our Engineering Team:
As a member of Foursquare’s engineering team, you will build complex products from the ground up. We're passionate about tackling tough challenges in the location space, and we’re seeking engineers who also like to dive deep into code and solve hard problems. You should be comfortable running with your own ideas and eager to learn new skills on a bleeding edge platform. We use a variety of tools, technologies, and languages to build software (Scala, Thrift, MongoDB, Memcached, JS/jQuery, Kafka, Pants, Hadoop, MR, Spark) but experience with equivalent ones will do just fine.
Join us and help bring our feature ideas (and your own!) off the whiteboard and into reality. As a Machine Learning Engineer, you will research improvements in data collection, feature engineering, and algorithmic optimization. You will also work on implementing your models in production systems and data pipelines. Here are some high-level applications of machine learning at Foursquare that you could work on within our Seattle office:
- Ingesting a variety of commercial activity data sources and applying model-building methods to improve our location intelligence technology
- Expanding on methods to learn from aggregated user activity data at scale with a variety of big data ML applications
- Investigating ways to improve the third dimension for location intelligence through feature engineering and incorporation of signals that go beyond GPS and WiFi
- Using NLP techniques to normalize, and infer structure from, unstructured place data from disparate sources
- Entity resolution and deduplication across of hundreds of millions of place records from providers
- Extracting the freshest and most correct information about a real-world place given data from publishers of varying quality
- Performing causal modeling and turning model outputs into real, actionable insights on a product that builds hundreds of machine learning models per day at scale to drive marketing decisions for many well-known companies and brands
- Masters (preferred Ph.D. degree) in Computer Science or a related technical field or equivalent practical experience
- 2+ years of work or educational experience in Machine Learning.
- Strong knowledge of ML techniques including both supervised and unsupervised learning, classification, regression, and optimization
- Proficiency in statistics
- Experience working with large, complex and diverse data sets from a variety of sources
- Ability to collaborate with a diverse set of engineers and data scientists
- Experience with one or more general-purpose programming languages including but not limited to: Java, C/C++, or Scala
- Experience with Hadoop, scalding, spark, or similar framework a plus
Foursquare is proud to foster an inclusive environment that is free from discrimination. We strongly believe in order to build the best products, we need a diversity of perspectives and backgrounds. This leads to a more delightful experience for our users and team members. We value listening to every voice and we encourage everyone to come be a part of building the company and products we love.
Foursquare is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.