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- Tasks: Lead the development of machine learning models to detect account takeovers and enhance cybersecurity.
- Company: Join Abnormal Security, a top-rated cybersecurity startup valued at $5.1 billion.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and innovation.
- Why this job: Make a real impact in protecting customers while working with cutting-edge technology.
- Qualifications: Strong background in machine learning, data science, and software engineering required.
- Other info: Mentorship opportunities available for junior team members.
The predicted salary is between 54000 - 84000 £ per year.
Abnormal Security is looking for a Senior Machine Learning Engineer to join the Account Takeover Detection team. At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine traditional approaches to Security. Abnormal is recognised as a top cybersecurity startup, securing a Series D funding of $250 million at a $5.1 billion valuation in August 2024. Our 100% YoY growth in annual recurring revenue highlights the trust our behavioural AI system has earned in protecting over 17% of the Fortune 500.
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 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 offers 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 while maintaining production models to ensure operational excellence and long-term strategy. 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.
Key Responsibilities- 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 and 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.
- 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.
- Familiarity with LLMs.
- Previous experience in Cybersecurity.
- Previous experience with Airflow or similar ML pipeline orchestration tools.
- Experience with large-scale ML systems and data infrastructure.
- Previous experience in behavioural modeling techniques.
- PhD or equivalent proven experience in ML research.
- Familiarity with cloud computing platforms (AWS, Azure).
Senior Machine Learning Engineer employer: Abnormal Security Corporation
Contact Detail:
Abnormal Security Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and cybersecurity. Since Abnormal Security is at the forefront of these fields, showcasing your knowledge of current technologies and methodologies can set you apart from other candidates.
✨Tip Number 2
Engage with the machine learning community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into the company culture and may even lead to referrals, increasing your chances of landing an interview.
✨Tip Number 3
Demonstrate your practical experience by working on personal projects or contributing to open-source initiatives related to machine learning and cybersecurity. This hands-on experience can be a great conversation starter during interviews and shows your commitment to the field.
✨Tip Number 4
Prepare to discuss how you've successfully implemented machine learning models in production. Be ready to share specific examples of challenges you've faced and how you overcame them, as this aligns closely with the responsibilities of the role at Abnormal Security.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Machine Learning Engineer position at Abnormal Security. Tailor your application to highlight relevant experiences that align with their focus on machine learning algorithms and cybersecurity.
Highlight Relevant Experience: In your CV and cover letter, emphasise your proven experience in machine learning, data science, and software engineering. Include specific projects or roles where you've developed and implemented machine learning models, especially in production environments.
Showcase Technical Skills: Clearly list your technical skills, particularly your proficiency with Python and machine learning toolkits like pandas and scikit-learn. If you have experience with MLOps or cloud computing platforms, make sure to mention these as they are highly relevant to the role.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your enthusiasm for the role and the company. Discuss how your background aligns with their mission to protect customers from account takeovers and your commitment to staying updated on the latest research in machine learning.
How to prepare for a job interview at Abnormal Security Corporation
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and tools like Python, pandas, and scikit-learn. Bring examples of projects where you've successfully implemented ML models, especially in production environments.
✨Understand the Company’s Mission
Familiarise yourself with Abnormal Security's focus on account takeover detection and their approach to cybersecurity. Demonstrating knowledge about their products and how your skills can contribute to their mission will set you apart.
✨Prepare for Problem-Solving Questions
Expect to tackle technical challenges during the interview. Practice explaining your thought process when developing machine learning solutions, including how you would approach feature engineering and model evaluation.
✨Emphasise Collaboration and Mentorship
Highlight your experience working in cross-functional teams and your ability to communicate complex ideas clearly. If you have mentorship experience, share how you've guided junior team members in their development.
