Senior Machine Learning Engineer, Abnormal Security

Account Takeover

Salary not provided

+ Equity

SQL
AWS
Python
Airflow
Tensorflow
Azure
Spark
Pandas
Scikit-Learn
PyTorch
Senior and Expert level
Remote in UK
Abnormal Security

Cloud email security platform

Open for applications

Abnormal Security

Cloud email security platform

501-1000 employees

B2BArtificial IntelligenceSaaSCyber SecurityCloud ComputingFraud

Open for applications

Salary not provided

+ Equity

SQL
AWS
Python
Airflow
Tensorflow
Azure
Spark
Pandas
Scikit-Learn
PyTorch
Senior and Expert level
Remote in UK

501-1000 employees

B2BArtificial IntelligenceSaaSCyber SecurityCloud ComputingFraud

Company mission

To make the cloud a safer place for businesses.

Role

Who you are

  • The ideal candidate will have a strong background in machine learning, data science, and software engineering, with the ability to design, develop, and implement robust machine learning models and systems in production
  • Proven experience as a Machine Learning Engineer or similar role
  • Strong knowledge of machine learning algorithms, statistics, and predictive modeling
  • Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally pytorch/tensorflow
  • Experience with machine learning operations (MLOps) and productionization of ML models
  • Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business questions and assess system efficacy
  • Ability to communicate complex technical ideas in a clear, non-technical manner

Desirable

  • 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
  • PhD or equivalent proven experience in ML research
  • Familiarity with cloud computing platforms (AWS, Azure)

What the job involves

  • Abnormal Security is looking for a Senior Machine Learning Engineer to join the Account Takeover Detection team
  • In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Account Takeover team (ATO) is at the forefront of customer protection, playing a central role in building systems that can detect malicious activity and protect customers from account takeovers
  • The Account Takeover Detection team’s mission is to leverage cutting-edge machine learning technologies for proactive detection and prevention of account takeover attempts, continuously improving ATO capabilities to stay ahead of evolving fraud patterns and safeguard user accounts with unparalleled accuracy and efficiency
  • This role will have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team
  • You will be involved in defining the technical roadmap required to address the most pressing customer problems and simultaneously, maintain production models ensuring operational excellence as well as long term strategy
  • Lead the development of machine learning algorithms and models for behavioural modeling and cybersecurity attack detection
  • Collaborate 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 & product engineers to productionize models and new ML based features
  • Actively monitor and improve production models through feature engineering, rules and ML modeling
  • Participate in code reviews and ensure high quality and maintainability of ML systems
  • Stay updated on the latest research in the field of machine learning, data science, and AI
  • Contribute to the development of machine learning best practices within the organization
  • Provide mentorship and guidance to junior team members

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Insights

Top investors

11% employee growth in 12 months

Company

Company benefits

  • Healthcare
  • Flexible PTO
  • 401k
  • One Medical
  • Flexible Spending Account
  • Mental Health Resources
  • Home Office Stipend
  • Monthly Internet & Phone Stipend
  • Health and Wellness Stipend

Funding (last 2 of 4 rounds)

Aug 2024

$250m

SERIES D

May 2022

$210m

SERIES C

Total funding: $534m

Our take

Fraud involving impersonation is one of the top causes of online financial crime. Criminal tactics like email account spoofing, where the criminal impersonates an official account to steal personal information or money, are rife. Abnormal Security is a startup aimed at handling these hyper-targeted and personalized email attacks by analyzing communications and identifying potential fraud before it can take place.

The fraud detection space is extremely competitive but Abnormal Security differentiates itself through its focus on the threat of impersonation rather than a spectrum of threats. This has allowed it to amass a wealth of data relating specifically to high-risk impersonation attacks, analyzing over 45,000 signals to detect any anomalies.

Its specialized approach has fueled rapid growth, leading to a $4B valuation after a Serice C Funding round. Now, Abnormal plans to double down on product development and expand internationally, prioritizing markets where data security laws necessitate a local presence. By staying focused on impersonation, Abnormal Security positions itself as a formidable force in the fight against online financial crime.

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Freddie

Company Specialist at Welcome to the Jungle