What are the responsibilities and job description for the Staff Machine Learning Engineer position at Zscaler?
Our Engineering team built the world's largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy.
We're hiring a talented Staff Machine Learning Engineer to join our growing ML/AI team at Zscaler. The team focuses on various cybersecurity use cases including threat detection, policy recommendation, malware detection, content classification, and anomaly detection. In this role, you'll have the opportunity to work on innovative ML/AI projects that address important cybersecurity challenges. Reporting to the Sr. Director, Machine Learning, you'll be responsible for:
- 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 techniques and architectures to solve complex cybersecurity problems.
- Collaborating with cross-functional teams to define project requirements and ensure alignment with business objectives.
- Staying updated on the latest advancements in machine learning and applying them to our cybersecurity solutions.
What We're Looking for (Minimum Qualifications)
- 5 years of experience as a Machine Learning Engineer, with a proven track record of delivering successful projects, with at least 2 years of experience working on cybersecurity products/projects.
- Strong proficiency in Python, SQL, and Object-Oriented programming.
- Extensive experience in feature engineering, model development, and error analysis.
- Solid understanding of machine learning concepts and their applications in cybersecurity.
- Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's Degree or PhD preferred).
What Will Make You Stand Out (Preferred Qualifications)
- Experience building LLM agents, fine-tuning, and/or evals at-scale as well as familiarity with unsupervised learning techniques, particularly clustering algorithms.
- Experience with public cloud services (such as AWS, Google Cloud, or Azure) and ML automation platforms.
- Contributions to the machine learning community through blog posts, tech talks, or publications.
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