Catch a fraudster if you can. Your challenge is to build distributed systems that sustain fraud attacks and imaginative ways fraudsters try to go around to do bad things. You will work closely with Sr SDEs and machine learning research scientists to design next generation fraud prevention systems utilizing the state of the art in machine learning, streaming applications, graph databases, workflows and serverless solutions.
You will get a chance to learn and utilize various technologies that power our applications, such as EMR, EC2, SWF, Sagemaker, Kinesis, and datasources from NoSQL databases like DynamoDB, traditional databases like MySQL/RDS/Aurora. On top of that you will get an opportunity to learn machine learning in partnership with our research scientists and apply ML to solve complex ambiguous problems. Can you imagine your career path with experiences you’ll obtain in building highly scalable web services, big data, and machine learning?
You should be someone who wants to build massively scalable, robust software, and wants to see your software thrive in the face of traffic from huge cloud computing services. You will drive the team’s direction and be encouraged to contribute towards our long-term vision and architecture.
The ideal candidate will have strong distributed systems and web services design and implementation experience, as well as experience working on high availability production systems. Machine learning experience is plus but not a must: you will get opportunity to learn this as part of the role.