FlightAware’s Predictive Technologies team is responsible for training and serving machine learning models to predict key flight elements. Our primary product is ETA predictions – en-route landing time (ON) and gate arrival time (IN) predictions
READ NOWJoining a new company brings opportunities to work on new projects, meet new colleagues, learn the company culture, and navigate its unique processes.
READ NOWFlightAware's summer intern program offers a number of benefits for both the company and the interns involved. For FlightAware, the program allows us to identify and recruit top talent, as well as gain fresh perspectives and insights from the next generation of engineers.
READ NOWMost opportunities for automation are discovered during day-to-day activity and recognizing repetitive processes. The FlightAware Desktop team is always looking for ways to improve processes, including automating repetitive tasks to reduce human error and to save time.
READ NOWMost of the posts on the Angle of Attack blog look to the past, but this post takes a different approach, as it speaks more to what FlightAware will do rather than what it has done. It will give readers some insight into how significant technical decisions are made at FlightAware.
READ NOWEach Summer during our town hall week, FlightAware engineers participate in our annual Hackathon. During the Hackathon, we take a break from our normal work to play around with technology, have some fun, compete against each other, and try to hack something amazing together.
READ NOWFlightAware’s picture of global flight activity emerges by fusing together information from dozens of disparate data sources.
READ NOWIn this blog post, we’ll provide an account of the problems that motivated FlightAware to adopt Nix and how we’ve used Nix to solve them at scale.
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