Machine Learning Engineer
🇺🇸 United States › New York › New York (Posted Jun 7 2018)
About the company
Since our inception in 2009, Foursquare has been a leading force in changing how location information enriches our real-world and digital lives. As a location intelligence company, Foursquare is comprised of two well-known consumer apps, Foursquare and Swarm, as well as thriving media and enterprise products. Our B2B offerings include Places (for developers), Pinpoint and Attribution (for marketers), and 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, and in sales offices around the globe, we’re dedicated to our trailblazing mission—enriching consumer experiences and informing business decisions with location intelligence.
As a member of Foursquare’s 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 and look for others who like to dive deep into code and help 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 NY office:
Ingesting a variety of commercial activity data sources and 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 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 tens of 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
Skills & requirements
Masters (preferred PhD degree) in Computer Science or 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
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