Senior Engineering Manager, Applied Machine Learning
Skills
- Proven leadership of applied ML or ML engineering teams
- Strong fundamentals in machine learning and statistics
- Designing statistically sound experiments and evaluations
- Experience building and operating production ML systems and pipelines
- Working with large-scale telemetry and time-series data
- Translating ML work into product value with cross-functional partners
- Clear technical communication for technical and executive audiences
Responsibilities
- Lead and grow a multidisciplinary team of data scientists and ML engineers focused on behavioral detection.
- Define and execute applied ML strategy for behavioral detection within the NDR product.
- Drive research, model evaluation, experimentation, and disciplined validation practices.
- Own production ML systems including model lifecycle management, data pipelines, and monitoring.
- Collaborate with Product Management and Security Research to convert models into analyst-facing detection signals.
- Influence product roadmap by identifying ML-driven opportunities to improve detection quality and analyst productivity.
- Mentor senior individual contributors and cultivate a culture of scientific rigor and technical ownership.
- Communicate technical strategy and model outcomes to senior leadership and cross-functional stakeholders.
Education
- Bachelor’s degree in Computer Science, Statistics, Machine Learning, or related quantitative field required
- Advanced degree (MS/PhD) in related field preferred
Benefits
- Health, dental, and vision benefits
- Flexible PTO, prorated sick time, federal holidays, and paid volunteer time
- Annual discretionary bonus eligibility
- FSA and dependent care accounts, Employee Assistance Program
- Educational reimbursement
- 401(k) with employer match (or pension where applicable)
- Pet insurance (US only) and parental leave (US only)
- Hybrid and remote work model
Average salary estimate
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