Machine Learning Engineer II - Behavioral Security Products
About this role
The Account Takeover Detection team builds systems to detect malicious activity and safeguard user accounts against adversaries. Daily work involves designing, developing, and implementing robust machine learning models and systems in production to stop fraud patterns with high accuracy. Successful team members combine machine learning, data science, and software engineering skills to shape technical goals and maintain production models.
Operating within a rapidly growing cybersecurity environment, the group focuses on behavioral modeling and security attack prevention. Candidates who thrive here are comfortable translating complex requirements into effective machine learning solutions while collaborating across infrastructure and product engineering functions.
What you will do
- Contribute to the development of machine learning algorithms and models for behavioral modeling and cybersecurity attack detection.
- Work with cross-functional teams to understand requirements and translate them into effective machine learning solutions.
- Conduct exploratory data analysis, feature engineering, model development and evaluation.
- Work with infrastructure and product engineers to productionize models and new ML-based features.
- Monitor and improve production models through feature engineering, rules, and ML modeling as part of a team effort.
- Participate in code reviews to ensure the quality and maintainability of ML systems.
What you need
- Proven experience as a Machine Learning Engineer or similar role in a commercial environment with at least 3 years of background.
- Solid knowledge of machine learning algorithms, statistics, and predictive modeling.
- Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally PyTorch or TensorFlow.
- Awareness of machine learning operations and productionization of ML models best practice.
- Familiarity with building data and metric generation pipelines using tools like SQL or Spark.
- Ability to communicate technical ideas in a clear, non-technical manner.
Nice to have
- Familiarity with LLMs
- Previous experience in Cybersecurity
- Previous experience with Airflow or similar ML pipeline orchestration tools
- Experience with large scale ML system and data infrastructure
- Previous experience in behavioural modeling techniques
Skills and tech stack
Questions candidates ask
Where is the role located?
This position is listed as Remote - UK.
What background is required for this position?
Applicants need 3+ years of proven experience as a Machine Learning Engineer or similar role in a commercial environment. Candidates should also have proficiency in Python, machine learning algorithms, and MLOps practices.
What does the interview process involve regarding AI?
Abnormal AI uses AI-assisted tools to help the recruiting team prepare for candidate interviews by analyzing resume content and role requirements to suggest interview questions. These tools do not make hiring decisions or screen candidates automatically, and every decision is made by a person.