Sr Engineering Manager - Machine Learning Infra
About the Role
Abnormal Security is looking for a Senior Engineering Manager to lead the Detection Serving & Signals (“DS&S”) team. You and your team will be responsible for the platforms & systems that power our core Detection capabilities. These systems include:
- Tier 0+ email scoring services at Abnormal, which are in the critical path for Remediation in Abnormal’s Email Security Product.
- Abnormal’s Feature Store (Compass), which provide a feature engineering platform to make adding and changing features a fast, responsive, stable, and confident experience for engineers
- Infrastructure to support processing, viewing, and accessing Message Entities in both an offline and online fashion
The ideal candidate for this role will have experience in leading production engineering teams that build scalable distributed systems and high-throughput real-time solutions. While knowledge/passion for Security or Fraud is a plus, it isn’t a requirement to be a successful leader for this team; here you’ll use what you picked up while working in Ads (or Search, Recommendation, etc.) in novel & exciting ways - all in the name of making the world a safer place.
Who you are
- You set high standards and expectations for project execution for yourself and the whole team
- You want to leverage your experience in running high-scale, real-time serving systems to guide a team to build out a Platform that protects our Customers from the most advanced Email attacks
- You are results-oriented, value collaboration, self-motivated, and willing to adapt to change in a fast-moving environment.
- You operate within an agile environment, and provide leadership to adapt to dynamics in technology, industry, cyber threats, and our own business.
- You are Customer-obsessed: you are excited to customer needs with how your team provides impact
What you will do
- Drive collaboration with internal and external customers & stakeholders
- Ownership & operational leadership over the teams responsible for:
- The infrastructure supporting our core detection capabilities
- The online and offline signals platforms
- The online model serving systems
- The model training & feature stores for existing and future products
- Building foundational capabilities of the systems and signal processing to enable 10x scaling 10x faster
- Leading and growing a team of Engineers to support these efforts
- 5+ years of professional experience as a hands-on engineer (either MLE or SWE) building data-oriented products and/or ML systems/products
- 2+ years of managing production ML Ops (preferred), or ML-Adjacent Platform teams
- Experience with real-time, online, and/or high-throughput & low-latency distributed systems
- Knowledge of key ML Ops team technologies (Spark, Data platform and Data coordination, Hadoop, Hive, feature platform serving systems, ML training and ML serving platforms, etc.)
- Mentor & team amplifier - Has led teams of platform engineers and helped build out systems that make ML engineers 10x more effective.
- Customer obsessed: Working with our internal engineers to determine the systems and signals roadmap and balance against engineering needs. Meeting with customers to understand their needs and explain our engineering roadmap.
- Recruiting magnet - you are able to set up a hiring plan, attract senior engineers, outline the vision of the team and build out a large team.
- Knowledge of best practices across the ML Ops community
- High standards - sets high standards and expectations for project execution for themselves and the whole team.
Nice to Have
- Experience running an Feature platform that powers multiple ML-based products, and ability to guide a team technically in this respect
- Prior experience in Cybersecurity
- Prior experience at high-growth startups
At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.