Factual is a data company focused on understanding the physical world through location. To make this goal a reality, we take on novel problems with small, focused teams made up of brilliant people.

At Factual, we cultivate multidisciplinary engineering teams. Everyone is comfortable with wrangling data, but we expect each individual contributor to bring a unique skill or expertise to the table. You should be a fast-working, highly-focused individual who pays strong attention to detail, shows great leadership and organizational skills, and gets things done. Our team works with applied big data, applied machine learning, high throughput and low latency API's, algorithms, thoughtful architecture, lots of practical coding, and excellent peers.

Factual presents a rewarding mission, a steep learning curve, and no upper bound on the problems we solve. If this sounds intriguing, you might be just the person we’re looking for.

Must-Have Qualifications: 

• Ability to thrive in a startup environment, while wearing many hats.
• A strong desire to keep learning.
• Strong interest and intuition around cluster computing.
• Fluency in Java, Python, or Clojure.
• Strong algorithms and data structures knowledge.
• Experience in writing fast production code.
• Comfort with Unix and the command line.
• Degree in Computer Science or advanced, demonstrable skills and knowledge of theory

Nice-to-Have Qualifications: 

• Familiarity with Hadoop ecosystem and distributed programming models such as Map/Reduce and Spark.
• Machine Learning knowledge/experience.
• Applied knowledge of databases and database theory.
• Experience with AWS, Docker, Mesos or Kubernetes
• Strong written and verbal communication skills.
• The more of these, the better: Javascript, Scala, C++, Ruby, iOS, Android, React, Rails.

Cover letters (creative and personalized) will be deeply appreciated.