Position: Senior Software Engineer (Java), Product Engineering Team
Company: Alcor
Experience required: 5y
English level: intermediate

We believe that machine learning is the way to empower internet-scale businesses to prevent fraud and improve trust.

We are a group of software engineers and data scientists working on products to enhance trust and safety of the internet. By providing a clear, accurate assessment of risk at multiple points of the end-user journey, we enable businesses to eliminate losses from fraud, and create adaptive, frictionless experiences for end-users. You will have the opportunity to collaborate with strong engineers, product managers and designers to build highly available and real-time systems to detect and prevent fraud for our customers.

What we are looking for:
As a senior software engineer on the team that builds Sift’s Digital Trust and Safety Product, you will work closely with product managers, data scientists and other software engineers to deliver various product features, which are at the intersection of machine learning and distributed systems. Specifically, you will:

● Design and build highly scalable, distributed microservices that can handle hundreds of millions of events per day
● Design and build offline experimentation systems used to simultaneously evaluate tens of thousands of models
● Scale machine learning pipelines used to produce thousands of models derived from terabytes of data

What would make you a strong fit:
● 5+ years experience building distributed backend systems using Java, Scala, C#, C++, or other object-oriented languages
● 3+ years experience working with large datasets using Apache Spark, MapReduce, or similar technologies
● 3+ years experience with cloud infrastructure (e.g. GCP, AWS, Azure)
● Strong software engineering fundamentals, including data structures, algorithms, and distributed systems, and strong debugging, testing, and problem-solving skills.
● Strong communication & collaboration skills, and a belief that team output is more important than individual output
● You are a self-starter, with a quick learning curve.

 Bonus points:
● Experience with stream processing systems such as Apache Flink, Apache Beam, Dataflow, or similar technologies
● Experience with HBase, BigTable, Kafka, ZooKeeper.
● Familiarity with practical challenges in ML systems, such as feature extraction and definition, data validation, training, monitoring, and management of features and models.