Senior Software Engineer (Full-time Contractor position)

Sift is the leader in Digital Trust & Safety, helping businesses protect themselves and their customers from fraud and abuse. We combine machine learning, behavioral analytics, and cutting-edge AI to power trust and reduce friction across the internet’s most valuable platforms.

We’re looking for a Senior Software Engineer to join our Payment Protection team and help shape the future of Trust & Safety. By delivering clear, accurate risk assessments at key moments in the end-user journey, we enable businesses to prevent fraud losses while creating seamless, adaptive experiences for their customers.

Our R&D team includes more than 100 engineers, with over 40+ based in Ukraine.

Our Tech Stack:

Core technologies: Java 11, GCP, BigTable, Kafka, Apache Flink, Spark, Dataproc, Dataflow, gRPC.

Other components: AWS, Python 3, Apache Airflow, Athena, Snowflake, BigQuery, Ruby, Ruby on Rails.

Frontend: React.js.

We follow Scrum methodology with two-week sprints.

What We’re Looking For:

6+ years of experience building distributed backend systems with Java or Scala.
3+ years of experience working with large datasets using Apache Spark, MapReduce, or similar technologies.
3+ years of experience with cloud infrastructure (GCP, AWS, or Azure).
Strong software engineering fundamentals (data structures, algorithms, distributed systems) and excellent debugging, testing, and problem-solving skills.
Strong communication and collaboration skills, with a focus on team success.

Bonus Points For:

Experience with stream-processing frameworks (Apache Flink, Apache Beam, Dataflow, etc.).
Experience with HBase, BigTable, Kafka, ZooKeeper.
Familiarity with ML systems: feature engineering, data validation, training, monitoring, and model lifecycle management.

What You’ll Do:

Design and implement tools and processes to release new machine learning models quickly, safely, and with minimal disruption.
Participate in architecture discussions to ensure we can serve hundreds of ML models at thousands of QPS.
Build scalable, low-latency, high-throughput, fault-tolerant, and easily maintainable data pipelines for both batch and real-time systems.
Ensure our systems scale rapidly while adapting to evolving product needs.
Support, motivate, and collaborate with engineers and data scientists, fostering a productive and empathetic team environment.
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