Build DataVisor’s machine learning infrastructure with Java, Python, and scalable distributed systems expertise. This hands-on technical leadership work supports real-time fraud detection and training.

Within Platform Engineering, you will combine proprietary unsupervised machine learning technology with supervised algorithms. You will expand streaming and database systems, strengthen detection capabilities, and automate end-to-end training. The role also involves mentoring engineers, managing operational health, and evaluating AI-assisted tools for engineering workflows.

Key Responsibilities:
Expand streaming and database systems for detection workloads
Automate end-to-end training processes and pipelines
Identify technical risks, dependencies, and delivery trade-offs
Mentor engineers in design,



quality, and execution
Improve alert quality, incident follow-through, and root-cause prevention

Requirements:
Eight-plus years developing software in production settings
Two-plus years leading technical outcomes across teams
Robust knowledge of computer systems, relational databases, and SQL
Experience with multithreaded and concurrent applications
Hands-on Cassandra, Yugabyte, Flink, Spark, or Kafka experience

Bring platform engineering leadership and distributed data expertise to DataVisor’s machine learning and real-time detection systems.

📌 Staff Engineer Machine Learning Infrastructure Vancouver
🏢 DataVisor
📍 Vancouver