Zscaler is looking to enhance its cybersecurity solutions through advanced machine learning algorithms and techniques.
Requirements
- Strong proficiency in Python, SQL
- Extensive experience in data modeling, feature engineering, model development, and error analysis
- Solid understanding of mathematical machine learning concepts Game Theory, Reputation Systems, Dynamical systems, etc
- Experience developing scalable algorithms with expertise in unsupervised learning techniques and model explainability
- Strong background in public cloud services (e.g., AWS, Google Cloud, Azure) and ML automation platforms, with prior experience on cybersecurity projects/products
- Proficiency in Rust programming for high-performance applications and secure coding practices
Responsibilities
- Leading the design and development of ML components, cybersecurity applications and providing technical guidance to junior and mid-level engineers
- Optimizing existing machine learning pipelines for improved efficiency and scalability
- Exploring and experimenting with advanced machine learning algorithms, agents, and architectures to solve complex cybersecurity problems
- Collaborating with cross-functional teams to define project requirements and ensure alignment with business objectives
- Advancing the frontier in machine learning, and applying them to our cybersecurity solutions
Other
- 7+ years of experience as a Machine Learning Engineer/scientist, with a proven track record of delivering successful projects
- Bachelor's degree in Computer Science, Physics, Mathematics, or a related technical field (Master's Degree or PhD preferred)
- 3 days a week in-office work in San Jose, CA
