Lead Machine Learning Engineer
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The role
Own the data-driven defense strategy by translating vague security threats into concrete mathematical problems and validating hypotheses quickly.
Lead the evolution of threat detection with probabilistic modeling, graph analytics, and both supervised and unsupervised learning.
Mentor junior scientists and engineers, and build internal tooling, feature stores, and reusable libraries to accelerate delivery.
Deliver production-grade ML models with strong CI/CD, scalability, and adversarial resilience to reduce alert fatigue.
Work with high-volume logs using Spark/PySpark, Flink, Snowflake, Kafka, and orchestrate pipelines with Kubernetes and Airflow.
Explain complex statistical concepts to non-technical stakeholders, manage scope and timelines, and chart data-driven solutions without predefined roadmaps.
Lead the evolution of threat detection with probabilistic modeling, graph analytics, and both supervised and unsupervised learning.
Mentor junior scientists and engineers, and build internal tooling, feature stores, and reusable libraries to accelerate delivery.
Deliver production-grade ML models with strong CI/CD, scalability, and adversarial resilience to reduce alert fatigue.
Work with high-volume logs using Spark/PySpark, Flink, Snowflake, Kafka, and orchestrate pipelines with Kubernetes and Airflow.
Explain complex statistical concepts to non-technical stakeholders, manage scope and timelines, and chart data-driven solutions without predefined roadmaps.
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Remote workNo
CitySan Francisco, United States