Senior Software Engineer, Pilgrim Modeling & Ranking
Since our inception in 2009, Foursquare has been a leading force in changing how location information enriches our real-world & digital lives. As a location intelligence company, Foursquare is comprised of two well-known consumer apps, Foursquare & Swarm, as well as thriving media & enterprise products. Our B2B offerings include Places (for developers), Pinpoint & Attribution (for marketers), & Place Insights (for analysts, based on the world's largest foot traffic panel). With more than 200 people across our offices in New York, San Francisco, & in sales offices around the globe, were dedicated to our trailblazing missionenriching consumer experiences & informing business decisions with location intelligence.
About our Engineering Team:
As a member of Foursquares engineering team, we want you to bring experience building real products from the ground up. We're passionate about tackling tough challenges in the location space & look for others who like to dive deep into code & help solve hard problems. You should be comfortable running with your own ideas & eager to learn new skills on a bleeding edge platform. We use a variety of tools, technologies, & 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 & help bring our feature ideas (and your own!) off the whiteboard & into reality. As a Senior Software Engineer on the Pilgrim Modeling & Ranking team, you will research, implement, & deploy improvements in data collection, feature engineering & algorithmic optimization. While were not necessarily looking for a data engineer or ML engineer (although thats definitely a plus!), you would have the opportunity to work on building ML models & big data pipelines. Here are some high-level applications of machine learning at Foursquare that you could work on within our NY office:
- Ingesting a variety of commercial activity data sources & applying model-building methods to improve our snap-to-place 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 & incorporation of signals that go beyond GPS & WiFi
- Using NLP techniques to normalize, & infer structure from, unstructured place data from disparate sources
- Entity resolution & deduplication across of hundreds of millions of place records from tens of providers
- Extracting the freshest & most correct information about a real-world place given data from publishers of varying quality
- Performing causal modeling & 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 & brands
- Bachelors degree in Computer Science or related technical field or equivalent practical experience
- 7+ years of professional experience & an elevated level of software engineering capability
- Experience working with large, complex & diverse data sets from a variety of sources
- Ability to collaborate with a diverse set of engineers & data scientists
- Experience with one or more general purpose programming languages including but not limited to: Java, C/C++, or Scala
- Strong knowledge of ML techniques including both supervised & unsupervised learning, classification, regression, & optimization
- 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 & backgrounds. This leads to a more delightful experience for our users & team members. We value listening to every voice & we encourage everyone to come be a part of building a company & 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.