4 F-Secure Jobs

Hybrid Mode of Work

Key responsibilities :

Youll grow your skills by working on exciting challenges that combine software engineering and machine learning as part of our internal team, the Scam Decipherers. (If youre detail-oriented, include the phrase Scam Decipherers assemble! in your cover letter - we use it to spot sharp minds.):

- ML Pipeline Development : Contribute to building and maintaining ML pipelines that detect sophisticated threats in real-world environments

- Threat Intelligence Systems : Help develop systems that analyse large volumes of online queries, behavioural events, and suspicious files

- Model Monitoring : Implement frameworks for evaluating model performance and identifying when models need retraining

- LLM Implementation : Gain hands-on experience deploying and optimizing LLMs for security applications like threat intelligence analysis and phishing detection

What we are looking for :

- ML Pipeline Knowledge: Understanding of ML workflows and how they operate in production environments. Familiarity with the challenges of deploying ML models (even if from coursework or personal projects) Basic knowledge of how to monitor ML systems

- Cloud & Infrastructure Skills: Experience with cloud platforms (AWS, Azure, GCP) - even from academic or personal projects. Understanding of containerization concepts (Docker) Enthusiasm for infrastructure as code approaches

- Model Evaluation Understanding : Knowledge of common ML evaluation metrics and what they indicate. Ability to interpret model performance reports. Interest in learning how to detect and address model drift.

LLM Awareness :

- Basic understanding of how LLMs work and their applications

- Familiarity with concepts like prompt engineering

- Eagerness to learn about LLM deployment in production

- Engineering Fundamentals:

- Solid Python programming skills

- Experience with version control systems (Git)

- Understanding of basic CI/CD concepts

- Willingness to learn best practices for production code