Senior Engineering Manager, Applied Machine Learning

🕒 April 3

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ExtraHop

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🔒 Cybersecurity

🔐 Security

🏢 Enterprise

💰 $41M Series C on 2014-05

Cybersecurity • Security • Enterprise

ExtraHop is a company that specializes in providing security and network management solutions, leveraging real-time analytics to help organizations detect and respond to cyber threats. By utilizing machine learning and other advanced technologies, ExtraHop offers deep visibility into IT infrastructure, ensuring optimal performance and robust security. Their platform aids enterprises in monitoring traffic patterns and identifying unusual activities to protect against data breaches and other cyber risks.

📋 Description

• Lead and grow a multidisciplinary team of data scientists and software engineers building production machine learning models and supporting systems for behavioral detection. • Drive the research, development, evaluation, and operational monitoring of models that analyze large-scale network telemetry, including time-series and behavioral anomaly detection. • Establish high standards for experimental rigor across the team, including statistically sound experimentation, clear evaluation methodologies, and disciplined model validation. • Own the technical direction for production ML systems supporting behavioral detections, including experimentation frameworks, model lifecycle management, data pipelines, and monitoring. • Collaborate closely with Product Management and Security Research to translate machine learning capabilities into practical detection signals that improve SOC analyst workflows. • Influence the product roadmap by identifying opportunities where applied machine learning can materially improve detection quality and analyst productivity. • Mentor senior data scientists and engineers while fostering a culture of scientific rigor, intellectual curiosity, and technical ownership. • Represent the machine learning function in cross-organizational discussions and communicate technical strategy and outcomes to senior leadership. • Stay current with advances in machine learning research and engineering practices and guide the team in adopting techniques that meaningfully improve detection performance.

🎯 Requirements

• Bachelor’s degree or equivalent experience in Computer Science, Statistics, Machine Learning, or a related quantitative field; advanced degree preferred. • 5+ years experience leading applied machine learning or machine learning engineering teams delivering production systems. • Strong background in machine learning, statistics, or a related quantitative discipline. • Experience guiding experimental design, model evaluation strategies, and statistically rigorous decision making. • Experience building or operating production ML systems, including model lifecycle management, data pipelines, and monitoring. • Experience working with large-scale telemetry, time-series data, or behavioral modeling problems. • Demonstrated ability to partner with product and domain experts to translate machine learning capabilities into user-facing value. • Strong technical judgment and the ability to guide architecture and modeling decisions. • Experience mentoring senior individual contributors and building high-performing ML teams. • Exceptional communication skills; able to translate model performance, technical tradeoffs, and data science concepts for product, executive, and cross-functional audiences. • Consistent, reliable, and accountable in attendance and execution.

🏖️ Benefits

• Health, Dental, and Vision Benefits • Flexible PTO, Sick Time Prorated Based on Date of Hire, and All Federal Holidays (US Only) + 3 Days of Paid Volunteer Time • Non-Commissioned Positions may be eligible to participate in the Annual Discretionary Bonus Plan • FSA and Dependent Care Accounts + EAP, where applicable • Educational Reimbursement • 401k with Employer Match or Pension where applicable • Pet Insurance (US Only) • Parental Leave (US Only) • Hybrid and Remote Work Model