Why Join Us?

Join the forward-thinking CloudGuard AI Security team, where you’ll collaborate with leading architects and engineers to design, build, and secure next-generation AI-enabled public cloud environments.

As a Data Scientist, you will not only build and refine machine learning models and analyze large-scale datasets but also take an active part in the coding effort and in developing production-grade components that power CloudGuard’s AI Security products.

Key Responsibilities

• Develop AI Security Insights – Leverage advanced statistical and machine learning techniques to detect threats, anomalies, or vulnerabilities in AI-driven cloud environments.
• Build, Code & Optimize ML Solutions – Design, implement, and optimize ML and LLM-based models using clean, maintainable, and efficient code; integrate them into CloudGuard’s product pipelines to ensure scalability and reliability.
• End-to-End Product Development – Collaborate with backend and DevOps engineers to deploy, monitor, and scale ML components within microservices and cloud infrastructure.
• Data Exploration & Feature Engineering – Conduct deep dives into complex datasets from various sources, transforming raw data into actionable features for robust model development.
• Continuous Learning & Adapting – Stay current on the fast-paced AI landscape, enterprise use cases, and emerging threat vectors; adapt existing models and pipelines accordingly.
• Cross-Functional Collaboration – Work closely with other data scientists, product architects, software engineers, and security experts to translate business needs into production-ready, data-driven solutions.
  
  

Qualifications

• B.Sc/M.Sc. or higher in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Data Science & Machine Learning: Proven track record of building, testing, and deploying ML models (1-2 years recommended) using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Programming Skills: Strong proficiency in Python (required) and familiarity with Go or other backend languages (advantageous). Ability to write production-level code, collaborate through Git, and work with CI/CD workflows.
• Cloud Experience: Familiarity with AWS services (e.g., S3, Lambda, SageMaker, EKS/Kubernetes) for data storage, processing, and model deployment pipelines.
• Analytical Mindset: Strong statistical background and the ability to derive insights from complex, large-scale datasets.
  
  

Advantages

• LLM Expertise: Hands-on experience with large language models, vector databases, or related NLP frameworks.
• Security Knowledge: Understanding of cybersecurity concepts, threat detection, and best practices for secure ML pipelines.
• Go/Python Development Experience: Experience contributing to production systems and collaborating closely with engineers.
• Passion for AI Security: Eagerness to explore and tackle evolving challenges at the intersection of AI and cybersecurity.