Machine Learning Team Leader

We are taking security operations through an evolutionary leap with our knowledge-powered XDR. We are looking for a top-notch lead for our Machine Learning team, to resolve the toughest issue in cybersecurity: utilizing terabytes of data for detecting attacks and prioritizing threats. Built by ex-nation-state cyber experts who harness the power of AI, the Hunters platform intelligently correlates events from every organizational data source and security solution, revealing undetected threats in modern enterprises.We are an early stage, well-funded startup, backed by Snowflake, Okta Ventures, M12 (Microsoft investment arm), YL Ventures, Blumberg Capital, and US Venture Partners.
Team Responsibilities:
  • Map problems that can be solved by ML models and determine the most suitable model for each problem;
  • Tackle the challenges around multi-source alerts and threat signals correlation and prioritization;
  • Develop and evolve anomaly detection algorithms for malicious behavior;
  • Develop, train and test models, both in staging and production environments;
  • Lead the scalability effort using ML.
Team Leader Responsibilities:
  • Define the team’s research roadmap;
  • Team building – recruitment, training, etc.
  • Manage ML projects from research to production;
  • Tutor/coach/mentor researchers in the team, manage the professional development path for team members;
  • Communicate with stakeholders, management, and customers about the direction of the ML efforts in the team;
  • Communicate with Domain Experts to formalize what problems should be solved;
  • Work with researchers and big data engineers to define the required features.
  • 3+ years of experience in leading an AI/ML team.
  • 3+ years of experience in the intersection of AI/Data Science and the Cyber domain.
  • Experience with evaluating and continuously improving models in production environments;
  • Experience with managing one or more of the following in production environments:
  • Anomaly detection;
  • Time Series;
  • Semi Supervised Models, augmentation in any domain;
  • Node Embedding / Graph Embedding;
  • Community Detection.
  • Ability to read and understand academic papers;
  • Strong background in DevOps and Kubernetes;
  • Strong background in GraphDB, AWS Neptune;
  • Solid understanding of one of the following cloud environments: AWS, Azure, GCP.
If you think you’re a good match, even if you can’t tick all the boxes, contact us nonetheless!
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