Senior ML Ops Engineer
Core
Design, maintain, and improve high-performance data pipelines and ML workflows to support enterprise security products serving hundreds of millions of users.
Role type
Senior ML Ops Engineer
Builds
Data pipelines, data stores, and interfaces for ML engineers/researchers to build datasets on demand
Domain
Cybersecurity / Enterprise Security / Distributed Data Systems
Deliverable
production ML models | infrastructure
Required skills
Python, Kafka, SQL, NoSQL (Clickhouse), Kubernetes, CI/CD, containerization, microservice design, distributed data systems, feature engineering
Preferred skills
Machine learning fundamentals (training, inference), PyTorch, TensorFlow, cross-functional collaboration
Technologies
Kafka, Clickhouse, AWS, Azure, Kubernetes
Responsibilities
Maintain and extend data/ML workflows for high-velocity data; Provide interfaces for on-demand dataset building; Influence data storage and processing strategies; Collaborate with ML, frontend, and backend teams; Reduce time-to-deployment for dashboards and models; Establish best practices for efficient dataset usage; Work with large datasets under performance constraints
Seniority
Senior, hands-on IC
