ML Engineer II - Account Takeover Defender

Abnormal Security Corp.; United States; Remote; USD 80,000 - 120,000; Full time

Job summary

Abnormal AI in the United Kingdom is seeking a Machine Learning Engineer to join the Account Takeover Detection team. You will design and implement ML models and production systems that detect malicious activity and safeguard customer accounts.

You will collaborate with data scientists, software engineers, and product teams to translate requirements into scalable solutions, maintain production pipelines, and monitor model performance.

Qualifications

• 3+ years of experience as a machine learning engineer or similar role in a commercial environment.
• Strong knowledge of machine learning algorithms, statistics and predictive modeling.
• Proficiency with Python and ML toolkits like pandas, scikit-learn, and PyTorch/TensorFlow.

Responsibilities

• Contribute to development of ML algorithms and models for behavioral modeling and cybersecurity detection.
• Collaborate with cross-functional teams to translate requirements into ML solutions.
• Conduct exploratory data analysis, feature engineering, model development and evaluation.
• Productionize models with infrastructure & product engineers and maintain ML features.
• Monitor and improve production models through feature engineering and ML modeling.
• Participate in code reviews to ensure quality and maintainability of ML systems.
• Stay updated on latest research in ML, data science, and AI.
• Adopt and contribute to ML best practices within the organization.

Skills

3+ years experience ml engineering

Effective communication

Tools

Python

Pandas

Scikit-learn

PyTorch/TensorFlow

SQL / Spark

Job description

Abnormal AI in the United Kingdom is seeking a Machine Learning Engineer to join the Account Takeover Detection team. You will design and implement ML models and production systems that detect malicious activity and safeguard customer accounts.

You will collaborate with data scientists, software engineers, and product teams to translate requirements into scalable solutions, maintain production pipelines, and monitor model performance.