13 дней назад
Senior Software Engineer - Model Platform (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Software Engineer - Model Platform (AI): Building model serving infrastructure, real-time data pipelines, online feature serving services, and ML training platforms for an advanced detection engine with an accent on scalability, high-throughput processing, and ML engineering enablement. Focus on scaling distributed systems to 10x current traffic, supporting feature serving at 50K+ QPS, and improving offline/online equivalency and model training workflows.
Location: Remote - Canada
Company
develops technology for detecting and stopping previously undetectable email and cloud-based attacks.
What you will do
- Architect, build, deploy, and maintain model serving infrastructure for the Detection Engine.
- Scale model serving and data processing services to support 10x current traffic.
- Build platform capabilities for detecting rapidly generated AI attacks.
- Develop real-time and near-real-time streaming pipelines and online feature serving services.
- Build the ML training platform to improve MLE velocity and product precision and recall.
- Collaborate with machine learning engineering and data science teams, and mentor junior engineers.
Requirements
- 5+ years of experience as a Software Engineer or in a similar role, including hands-on ML engineering solutions.
- Experience maintaining large-scale distributed systems on AWS, GCP, or Azure.
- Experience with high-scale real-time and near-real-time data pipelines or streaming services.
- Familiarity with ML workflows, feature development and serving at 50K+ QPS, offline/online equivalency, and large batch jobs for training tree and deep learning models.
- Experience with streaming data architectures, real-time processing, security, and data privacy compliance.
- Strong collaboration, communication, problem-solving, and independent execution skills.
Culture & Benefits
- Remote work from Canada.
- Ownership-oriented role with direct impact on detection technology and ML platform capabilities.
- Collaborative work with data scientists, machine learning engineers, product managers, and other stakeholders.
- Structured mentoring through one-on-ones, pair programming, code reviews, and design reviews.
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