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Machine Learning Engineer II

Abnormal Security - Remote - USA

Posted Feb 4, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
Not verified
Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
Not verified
Verification
Not verified checked Jun 7, 2026
Salary
$161K-$231K From the posting source checked Jun 20, 2026
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

68% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026
Work mode
Remote From the posting source checked Jun 20, 2026
In-office days
0 days From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Series D From the posting source checked Jun 20, 2026
Equity
Offered From the posting source checked Jun 20, 2026

Application

Cover letter
Not verified
Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Engineer II Remote - USA About The Role Abnormal AI is looking for a 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 25% of the Fortune 500 ( 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 team is solving a multi-layered detection problem, which involves modeling communication patterns to establish enterprise-wide baselines, incorporating these patterns as robust signals, and combining these signals with contextual information to create extremely precise systems. The team builds discriminative signals at various levels including message level (eg. presence of particular phrases), sender-level (eg.frequency of sender) and recipient level (eg.likelihood of receiving a safe message).

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