Fortinet is looking for a Senior Data Scientist with expertise in Machine Learning (ML) and Large Language Models (LLMs) to enhance our cybersecurity solutions. In this role, you will design and implement a variety of ML techniques, including LLMs and other advanced algorithms, to analyze threats, automate processes, and improve detection and response systems. You will lead projects end-to-end, transforming research into scalable, high-impact solutions that secure our clients' digital environments.
Responsibilities
- Research, design, and implement ML-based solutions for cybersecurity applications, such as anomaly detection, behavior modeling, and threat intelligence analysis.
- Lead end-to-end projects, including research, implementation, deployment, and production monitoring.
- Leverage LLMs and other ML techniques, including clustering, classification, and time-series analysis, to develop innovative solutions for cybersecurity challenges.
- Fine-tune and perform prompt tuning to optimize LLMs for tasks like phishing detection, log analysis, and malware categorization.
- Develop scalable pipelines for data preprocessing, training, and deploying ML models in production environments.
- Collaborate with data engineers and software teams to build and maintain infrastructure for data collection, storage, and processing.
- Apply unsupervised and supervised learning techniques to detect emerging threats and patterns in large-scale cybersecurity data.
- Design robust APIs and services to integrate ML and LLM solutions into existing systems.
- Propose and prototype novel ML approaches to improve our products and internal workflows.
- Stay updated on advancements in ML, including LLMs, computer vision, and graph-based models, identifying opportunities to apply them in cybersecurity.
- Provide mentorship and technical guidance to junior data scientists and engineers.
- Work closely with an Incident Response team to improve real-time detection.
Requirements
- 4+ years of professional experience in ML Engineering (Advantage to GenAI) in an AI company that involves working with researchers.
- Proficiency in Python and ML packages
- Experience with AI/ML (MLOps) and a strong understanding of system architecture - Advantage
- Master's or Ph.D. in Computer Science, Statistics, Artificial Intelligence, Machine Learning, or a related field - Advantage
- Familiarity with vector databases, SQL/NoSQL systems, and API development.
- Strong problem-solving, critical thinking, and communication skills.