ML Detection Engineer, Information Security
- Cupertino, CA
Posted: Oct 13, 2020
Weekly Hours: 40
Role Number: 200197626
This position can be located in Santa Clara Valley (CA), Austin (TX), or Seattle (WA) Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! Apple Information Security is seeking a Detection Engineer with experience using Machine Learning or Statistics to help us keep Apple safe.
- 5+ years of proven track record in Information Security with focus on incident response, threat hunting, and crafting detection signatures.
- 1+ year of experience using statistics or machine learning techniques in the Information Security Domain
- Deep understanding of Incident Response, Cyber Kill Chain, Threat Modeling, and attack vectors. Familiarity with current threat detection tools and technologies.
- Experience with analysis of network traffic and usage of Deep Packet Inspection tools.
- Experience writing and tuning of IDS/IPS signatures.
- In-depth technical knowledge of macOS and Linux Operating Systems.
- Understanding of malware functionality and persistence mechanisms.
- Ability to analyze endpoint, network, and application logs for anomalous events.
- Practical experience working with and conducting experiments on very large datasets then turning prototypes into production detections/models.
The ideal candidate will possess a strong technical background and information security experience with a focus on detection using statistical or machine learning techniques. Additional responsibilities include: Provide feedback and enforce use case development lifecycle. Collaborate with teams to incorporate requirements, using log sources such as network, endpoint and application data to craft signatures/rules. Identify gaps in log data and recommend solutions to address said gaps. Perform security monitoring and incident response duties as needed
Education & Experience
PhD in Computer Science, Math, Statistics, Physics, or related field. Equivalent work experience will be considered.
- Strong programming skills in Java, Scala, or Python preferred
- Experience in practical software engineering standard methodologies is a plus
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