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    Machine Learning Engineer - San Francisco, California, United States - Job Board

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    Description

    By making evidence the heart of security, we help customers stay ahead of ever-changing cyber-attacks.

    Corelight is a cybersecurity company that transforms network and cloud activity into evidence. Evidence that elite defenders use to proactively hunt for threats, accelerate response to cyber incidents, gain complete network visibility and create powerful analytics using machine-learning and behavioral analysis tools. Easily deployed, and available in traditional and SaaS-based formats, Corelight is the fastest-growing Network Detection and Response (NDR) platform in the industry. And we are the only NDR platform that leverages the power of Open Source projects in addition to our own technology to deliver Intrusion Detection (IDS), Network Security Monitoring (NSM), and Smart PCAP solutions. We sell to some of the most sensitive, mission critical large enterprises and government agencies in the world.

    We are building a world class and uniquely targeted team to drive research through data science and security expertise. The ideal candidate will use their strong analytic skills and awareness of network and cloud security data to drive novel, durable, and effective threat detection. Corelight can define the data our sensors generate, you will have the opportunity to contribute to how we extend the data itself to enable new types of analysis as
    needed. You will be able to look back a year from now and say two things with pride: first, "I helped to build that." and second, "We are generating insights that no one else in the world has achieved."

    Opportunity

    • Work with Vern Paxson (creator of Zeek, UC Berkeley Professor and renowned network security researcher) and a world-class team of network security experts
    • Analyze TTPs (using live network traffic) to create data-driven, tunable models for behavioral detection with low FP rates. Iterate those models based on customer engagement
    • Specify improvements to the data itself (e.g. new / different protocol parsers, data augmentation) that will enable unique insights and superior threat detection
    • Drive advances in the analytics tools and frameworks (e.g. across structured detection algorithms, machine learning, artificial intelligence, behavioral analysis) both for our growing research team and in the Corelight Sensor, to create and execute those models
    • Work closely with product management and engineering to guide implementation of the data and analytics improvements into the core product
    • Author key materials to share (a) network security insights with the security community, and (b) guide customers in employing your security components

    Qualifications

    • MS in Computer Science or Engineering, or equivalent experience. Cloud security certifications are preferred
    • Strong knowledge of building and securing cloud environments both virtual and containerized. Working knowledge of investigation and incident response processes for cloud environments. AWS experience is preferred, with Azure and GCP also beneficial
    • Strong structural modeling, machine learning and/or statistical modeling expertise, including applying the techniques to real world problems. Experience with tools and environments such as Zeek, R, Python/Pandas, Matlab/Octave, Tensorflow, Spark
    • Knowledge of corporate security investigation and incident response processes, especially in cloud environments. Awareness of threat TTP's including the MITRE ATT&CK Framework
    • Working knowledge of cloud infrastructure such as containerization, deployment via infrastructure as code, service meshes
    • Networking: Working knowledge of networking concepts and network protocols such as TCP/IP, HTTP, TLS, DNS
    • Coding: Experience coding across common languages

    We are proud of our culture and values - driving diversity of background and thought, low-ego results, applied curiosity and tireless service to our customers and community. Corelight is committed to a geographically dispersed yet connected employee base with employees working from home and office locations around the world. Fueled by an accelerating revenue stream, and investments from top-tier venture capital organizations such as Crowdstrike, Accel and Insight - we are rapidly expanding our team.

    Check us out at



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