Senior Machine Learning Engineer

3 days ago

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Censys

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Cybersecurity • Enterprise • Data

Censys is a leading Internet Intelligence Platform that specializes in Threat Hunting and Attack Surface Management. It provides security teams with a comprehensive, accurate, and up-to-date map of the internet to defend against attacks and hunt for threats. Censys offers solutions for Cloud Asset Discovery, Exposure and Risk Management, and External Attack Surface Management. Its proprietary Internet Map delivers detailed insights and extensive internet scanning capabilities, allowing organizations to continuously monitor internal and external attack surfaces. Founded by the creators of ZMap at the University of Michigan, Censys is deeply rooted in the security open source community and boasts a large internet intelligence community. Censys empowers organizations, including those in financial services, government, and healthcare, to act swiftly against evolving threats and protect their internet-facing assets effectively.

51 - 200 employees

Founded 2017

🔒 Cybersecurity

🏢 Enterprise

📋 Description

• Deploy and maintain containerized workloads to support machine learning development, deployment, and post-deployment monitoring. • Utilize tools like helm and kustomize to accelerate the deployment of machine learning models and data pipelines. • Apply various optimization techniques such as compilation, quantization-aware-training (QAT), and pruning to improve latency and throughput of models. • Utilize open-source software like Metaflow, Prefect, Temporal, and Argo Workflows to facilitate data science development. • Build and optimize machine learning models to analyze security data, extract actionable insights, and identify trends, anomalies, and other relevant security signals. • Develop and maintain systems for drift detection and model monitoring to ensure continuous improvement and accuracy of insights. • Collaborate with cross-functional teams to design data pipelines that can efficiently process petabytes of raw internet security data.

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or other technical discipline (or equivalent professional experience). • 3+ years of experience in docker, kubernetes and helm. • Strong proficiency in python and machine learning libraries like PyTorch, Transformers, and Timm. • Proficiency in MLOps tooling like Metaflow, MLflow, Argo Workflows, torchrun and Ray. • Experience working with cloud platforms like AWS, GCP, and Azure.

🏖️ Benefits

• 401k match • health • vision • dental • and more!