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Description:
Research, design, and develop data schema and normalization for integration of third-party security data.
Transform detection use cases and requirements into machine learning problems for security enhancements.
Develop efficient machine learning algorithms for security detection, correlation, and investigation.
Implement product features for security detection, correlation, and investigation.
Establish processes, tools, and metrics to monitor and evaluate detection efficacy for customers.
Requirements:
Master’s or Ph.D. degree in Computer Science or related field with a focus on machine learning, deep learning, natural language processing, or artificial intelligence.
Proven experience in Machine Learning Engineering or Research with expertise in time series analysis, graph machine learning, and natural language processing.
Familiarity with tools and frameworks for building machine learning applications.
Strong understanding of machine learning algorithms, statistical models, and deep neural networks.
Excellent problem-solving skills and ability to translate research into practical solutions.
Proficiency in Python for quick design and implementation of proof of concepts.
Strong communication skills to convey complex ideas to technical and non-technical audiences.
Preferred: Knowledge or experience in cybersecurity, security products, and open-source data models.