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- Tasks: Develop cutting-edge machine learning models to protect customers from account takeovers.
- Company: Join a top cybersecurity startup recognised for innovation and growth.
- Benefits: Competitive salary, health benefits, remote work options, and career development opportunities.
- Other info: Dynamic team environment with excellent opportunities for professional growth.
- Why this job: Make a real impact in cybersecurity while working with advanced technologies.
- Qualifications: 3+ years in machine learning, strong Python skills, and a passion for data science.
The predicted salary is between 60000 - 80000 £ per year.
Abnormal AI is looking for a 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 the traditional approaches to Security. Our 100% YoY growth in annual recurring revenue highlights the trust our behavioral AI system has earned in protecting over 20+% of the Fortune 500. We continue to grow and innovate to stay ahead of the evolving threat landscape.
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 offers the opportunity to contribute significantly to our team's charter, direction, and roadmap by defining technical goals, addressing customer problems, maintaining production models, and ensuring operational excellence. The ideal candidate will have a 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:- 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.
- Stay updated on the latest research in the field of machine learning, data science, and AI.
- Adopt and contribute to the development of machine learning best practices within the organization.
- Proven experience as a Machine Learning Engineer or similar role in a commercial environment (3+ years).
- Knowledge of machine learning algorithms, statistics, and predictive modeling.
- Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally, pytorch/tensorflow.
- Awareness of machine learning operations (MLOps) and productionization of ML models best practice.
- 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 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 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).
Machine Learning Engineer II - Behavioral Security Products employer: Abnormal
Contact Detail:
Abnormal Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer II - Behavioral Security Products
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to cybersecurity. We want to see your work in action, so make sure it’s easy to access and highlights your best achievements.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practicing common machine learning scenarios and being ready to discuss your past experiences in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team at Abnormal AI.
We think you need these skills to ace Machine Learning Engineer II - Behavioral Security Products
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with machine learning algorithms, data science, and any relevant projects that showcase your skills in cybersecurity. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about behavioural security and how your background aligns with our goals at Abnormal AI. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Projects: If you've worked on any interesting machine learning projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see how you've applied your skills in real-world scenarios. Don't be shy – share your successes!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re genuinely interested in joining our team at Abnormal AI!
How to prepare for a job interview at Abnormal
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning algorithms and models. Be ready to discuss your experience with tools like Python, pandas, and scikit-learn. They’ll likely ask you about specific projects you've worked on, so have a couple of examples ready that showcase your skills in developing and implementing ML solutions.
✨Understand the Cybersecurity Landscape
Since this role is focused on behavioural security products, it’s crucial to understand the current trends and challenges in cybersecurity. Familiarise yourself with account takeover tactics and how machine learning can help combat them. Showing that you’re aware of the evolving threat landscape will impress the interviewers.
✨Communicate Clearly
You’ll need to explain complex technical concepts in a way that non-technical team members can understand. Practice articulating your thoughts clearly and concisely. Think about how you would explain your past projects or the importance of certain algorithms to someone without a technical background.
✨Show Your Team Spirit
Collaboration is key in this role, so be prepared to discuss how you’ve worked with cross-functional teams in the past. Highlight any experiences where you’ve contributed to team goals or helped improve processes. This will demonstrate that you’re not just a great engineer, but also a team player who can drive success together.