About
Design and implement production-grade machine learning systems for cloud and on-premises environments Build and optimize ML model architectures for cybersecurity use cases, including threat detection and anomaly detection Develop data pipelines and ML workflows that support real-time and batch processing requirements
Required Qualifications
6+ years of engineering experience with at least 4 years focused on machine learning in production environments Strong software engineering foundation with expertise in Python and SQL, plus experience in another language (Go, Rust, Java, etc.) Experience building and deploying ML systems using frameworks like scikit-learn, PyTorch, or TensorFlow Familiarity with MLOps practices, including model versioning and monitoring in high-reliability environments Knowledge of containerized deployment solutions and cloud-native architectures
Languages
- English
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