We are looking for a Senior Data Scientist with deep expertise in Large Language Models (LLMs), Deep Learning, and Neural Networks to join our Threat Research group, located in our Tel Aviv Office. Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for new products, and drive innovation and thought leadership in cybersecurity.
Key Responsibilities :
Serve as the technical lead for projects involving LLMs, deep learning, and neural networks focused on cybersecurity applications.
Design, train, fine-tune, and deliver LLMs and advanced deep learning models for tasks such as anomaly detection, threat classification, and automated analysis of security data.
Drive hands-on research from ideation through prototyping to scalable production systems.
Collaborate with product and engineering teams to integrate advanced AI models into security solutions.
Analyze complex, high-dimensional security data (including text, logs, network traffic, and more) to identify emerging threats and attack patterns.
Mentor and guide other data scientists and contribute to the teams technical growth.
Represent in the AI and security communities through thought leadership, publications, presentations, and patents.
Requirements: 7+ years of hands-on experience in machine learning and deep learning, with a strong focus on neural networks and NLP, including proven work on high-scale, production-level projects.
At least 3 years of proven experience in training, fine-tuning, and delivering LLMs and deep learning models at scale.
Advanced proficiency with Python and leading ML/DL frameworks: PyTorch, TensorFlow, Keras, etc.
Experience with MLOps, scalable model deployment, and optimizing inference for production environmnts.
Strong background in analyzing large, complex datasets using SQL, Spark, or similar tools.
Track record of delivering impactful AI solutions in real-world settings.
Experience in application/data security is a strong advantage.
Experience with cloud platforms (AWS, Azure, GCP) is a plus.
Experience with Kubernetes (K8s) and microservices infrastructure is a plus.
Experience with CI/CD practices and the full lifecycle of ML model development, from data preparation to deployment and monitoring, is a strong advantage.
Ph.D. or M.Sc. in Computer Science, Engineering, Math, or another quantitative/technical field is valued, but not required if you have strong relevant professional experience.
Excellent communication, mentoring, and collaboration skills.
This position is open to all candidates.