Position: Senior Software Engineer (Java), Product Engineering Team
Company: Alcor
Experience required: 5y
Category: Java
English level: intermediate
Published: 2022-05-01T00:00:00+03:00

About the team:
The Product Engineering team is a group of software engineers and data scientists working on products to enhance the 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.

Our R&D team consists of over 100 engineers, and 30+ are based in Ukraine. Product Engineering consists of several fraud products including Account Defense, Payment Protection, Content Integrity, and Dispute Management. We are building a fully staffed engineering team for each of these products in Ukraine. These teams will work in close collaboration with colleagues from other R&D offices.

Tech stack:

Java 11
GCP
BigTable
Kafka
Apache Flink
Spark
Dataproc
Dataflow
gRPC
Other Sift Components Tech stack - AWS, Python 3, Apache Airflow, Athena, Snowflake, BigQuery, Ruby, RoR, FE: React.js.

We use Scrum and 2 weeks sprints.

Opportunities for you:

Professional growth: quarterly Growth Cycles instead of performance review
Experience: knowledge sharing through biweekly Tech Talks sessions. You will learn how to build projects that handle petabytes of data, have small latency and high fault tolerance
Business trips and the annual Sift Summit, in 2022 Summit takes place in California
Hybrid work approach: you can choose where you work better remotely or in the office
What would make you a strong fit:

5+ years of experience building distributed backend systems using Java, Scala, C#, C++, or other object-oriented languages
3+ years of experience working with large datasets using Apache Spark, MapReduce, or similar technologies
3+ years of 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
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
What you’ll do:

Design and build tools and processes to make the release of new machine learning models fast, easy, safe, and minimally disruptive
Participate in architecture discussions to meet the requirement to serve hundreds of machine learning models at thousands of queries per second
Ensure that our systems can continue to scale rapidly while addressing rapidly evolving product team needs.
Implement scalable, low-latency, high-throughput, fault-tolerant, extensible, and easily maintainable data processing pipelines for both batch and real-time systems
Motivate, listen and empathize, and help engineers and data scientists to excel
A little about us:

Sift is the leading innovator in Digital Trust & Safety. Hundreds of disruptive, forward-thinking companies like Zillow, and Twitter trust Sift to deliver outstanding customer experience while preventing fraud and abuse.

The Sift engine powers Digital Trust & Safety by helping companies stop fraud before it happens. But it’s not just another anti-fraud platform: Sift enables businesses to tailor experiences to each customer according to the risk they pose. That means fraudsters experience friction, but honest users do not. Sift allows businesses to scale, win, and thrive in the digital era by drawing on insights from our global network of customers.

Benefits and perks:

A compensation package that consists of financial compensation, a biannual 5% bonus, and stock options
Medical, dental, and vision coverage
50$ for sports and wellness
Education reimbursement: books, education courses, conferences
Flexible time off: we follow an unlimited vacation approach
Tuned work schedule to Kyiv timezone despite US offices location: biweekly demo sessions are optional for our team and we watch them from recording
Mental Health Days: additional 4 day-offs
English courses and social activities inside the company that allow improving your public speaking and language