Abnormal SecurityAS

Staff Machine Learning Engineer

Abnormal Security uses behavioral AI and ML models to learn the behavior of all employees and partners.

Abnormal Security

Employee count: 501-1000

Salary: 230k-270k USD

United States only

About the Role

Abnormal Security is looking for a Staff Machine Learning Engineer to join the Message Detection - Attack Detection team. At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. That’s what makes our novel behavioral-based approach so…Abnormal. Abnormal has constantly been named as one of the top cybersecurity startups and our behavioral AI system has helped us win various cybersecurity accolades resulting in being trusted to protect more than 17% of the Fortune 1000 ( and ever growing ).

In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories.

This role is central to our mission of protecting the world’s largest enterprises. You will be responsible for reasoning about the gaps in our multi-layered detection system and proposing generalizable ML solutions. You will have a significant impact on our technical roadmap, guiding how our diverse set of detection models—spanning behavioral analysis, natural language understanding, and deep learning systems—work in concert. This is a unique opportunity to shape the future of our ML architecture, from evolving our core training and deployment strategies for a global infrastructure to defining how our core ML capabilities can be exposed as scalable services to power other products across the company.

What you will do

  • Serve as a technical leader and subject matter expert, providing architectural guidance and mentorship across multiple machine learning workstreams.
  • Architect and design generalizable ML systems to address the most critical gaps in our detection capabilities, moving beyond incremental improvements.
  • Reason holistically about our entire detection engine, defining the architectural vision for how different classes of models—from heuristic and behavioral to complex deep learning systems—should integrate and operate.
  • Drive the technical roadmap for foundational, long-term projects, such as evolving our global model training paradigms and creating centralized ML capabilities that can be leveraged as platforms by other teams.
  • Provide technical mentorship and feedback on ML decisions across different workstreams, elevating the performance of the entire team.
  • Own the end-to-end ML lifecycle: from data analysis, feature engineering, and model prototyping to working with infrastructure teams on productionization, deployment, and monitoring of large-scale models.
  • Investigate complex model performance issues, applying a deep theoretical understanding of machine learning and deep learning to diagnose and resolve them.
  • Continuously adapt our systems to new, unseen attacks by developing and refining our automated model retraining and evaluation pipelines.

Must Haves

  • 8+ years of experience designing and building high-impact, customer-facing machine learning applications.
  • Proven experience working on ML at scale with direct product impact in mature ML industries such as recommendation systems, ad tech, quantitative finance, or fraud detection.
  • Strong grasp of the theoretical limitations of deep learning models and a systematic approach to investigating and debugging poor model performance.
  • Demonstrated experience in the productionization of large-scale ML models in fast-feedback environments.
  • Ability to reason about abstract system gaps and propose generalizable, architecturally sound ML solutions, not just point fixes.
  • Expertise across the entire ML lifecycle, from data exploration and feature engineering to model deployment and online scoring.
  • Fluency in Python and ML frameworks like Scikit-learn, PyTorch, or TensorFlow.
  • BS degree in Computer Science, Applied Sciences, Information Systems, or a related engineering field.

Nice to Haves

  • MS or PhD degree in Computer Science, Electrical Engineering, or another related engineering/applied sciences field.
  • Experience leading multi-quarter, cross-functional ML projects.
  • Experience with MLOps tools and building scalable data pipelines.

This position is not:

  • A research-oriented role that's two-steps removed from the product or customer

At Abnormal AI, 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.

Base salary range:$229,500—$270,000 USD

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

About the job

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Posted on

Job type

Full Time

Experience level

Senior

Salary

Salary: 230k-270k USD

Location requirements

Hiring timezones

United States +/- 0 hours

About Abnormal Security

Learn more about Abnormal Security and their company culture.

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Abnormal Security uses behavioral AI and ML models to learn the behavior of all employees and partners. This approach allows Abnormal to stop the full spectrum of email attacks—credential phishing, business email compromise, vendor invoice fraud, and more—as well as emerging attack types across email and collaboration apps.

We are driven to deliver frictionless user experiences while building a durable platform that will continue to offer the highest efficacy protection for our customers. That’s why customers trust us to keep their cloud email secure.

The Abnormal leadership team is composed of visionaries with decades of AI and ML experience, dedicated to delivering an exceptional customer experience. Their careers span influential roles at companies like Google, Twitter, Amazon, Proofpoint, Okta, Salesforce, and Slack.

Employee benefits

Learn about the employee benefits and perks provided at Abnormal Security.

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Virtual lunch budget

Monthly virtual lunch budget for employees

Paid parental leave

12 weeks paid maternity and paternity leave

Unlimited PTO

Regular salaried team members enjoy unlimited PTO

Pre-tax commuter benefits

Employees can contribute pre-tax for public mass transit

View Abnormal Security's employee benefits
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Abnormal Security

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Abnormal Security hiring Staff Machine Learning Engineer • Remote (Work from Home) | Himalayas