Remote job
Senior Software Engineer - Model Platform
Job details
About this role
Role overview
The Senior Software Engineer, Model Platform will build and operate the infrastructure that supports machine-learning detection systems for email and cloud-based threats. This is a platform engineering role focused on high-scale serving, streaming data, online feature delivery, and training workflows, with substantial ownership of architecture, reliability, and developer velocity.
Responsibilities
- Architect, implement, deploy, and maintain model-serving infrastructure for a production detection engine. - Scale model-serving and data-processing services to support substantially higher traffic and demanding availability requirements. - Build systems that help detect emerging attacks, including threats generated or amplified by artificial intelligence. - Own real-time and near-real-time streaming pipelines together with online feature-serving services. - Improve machine-learning training infrastructure to increase model-development speed and product precision and recall. - Partner with machine-learning and data-science teams, and mentor engineers through design reviews, code reviews, pairing, and regular coaching.
Requirements
- Five or more years of software engineering experience, including hands-on work supporting machine-learning systems. - Experience operating large-scale distributed systems on AWS, GCP, Azure, or comparable cloud platforms. - Background maintaining high-volume real-time or near-real-time data pipelines and streaming services. - Familiarity with machine-learning workflows such as online feature serving, offline/online consistency, and large batch jobs for training tree-based or deep-learning models. - Experience with streaming architectures, real-time processing, and engineering practices for reliable cloud services. - Strong independent problem-solving skills and the ability to turn ambiguous requirements into practical, scalable solutions.
Nice to have
Experience supporting feature development and serving at approximately 50,000 queries per second, along with knowledge of security, compliance, data privacy, and the operational needs of data-science and machine-learning teams.