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.
At Zscaler, our ML/AI teams focus on various cybersecurity use cases including threat detection, policy recommendation, malware detection, content classification, and anomaly detection.
We're looking for an experienced Sr. Staff Machine Learning Engineer to join our team.
You will have the opportunity to work on cutting-edge ML/AI/LLM development projects that address complex cybersecurity challenges.
Reporting to the Director, Machine Learning & AI, you'll be responsible for:
Leading the development of advanced machine learning models to address complex business problems and communicate complex data science concepts to non-technical stakeholders and drive data-driven decision-making across the organization.Mentoring and guiding team members on projects and professional growth.Designing, implementing, and evaluating innovative machine learning solutions, while ensuring alignment with business objectives.Driving strategic initiatives, identifying opportunities for improvement and innovation and collaborating with cross-functional teams to define project objectives and deliverables.Applied research: Stay up-to-date and apply the latest advancements in machine learning and data science.What We're Looking for (Minimum Qualifications) 7+ years of experience as a Machine Learning Engineer, with a proven track record of leading and delivering successful projects along with 3+ years of experience in cyber security products/projects.Expertise in Python (e.g., Pandas, Sklearn, TensorFlow, PyTorch), SQL, and Object Oriented programming with extensive experience in feature engineering, model evaluation, and error analysis.In-depth knowledge of Large Language Models (LLMs) and their applications along with a strong passion for leveraging ML/AI to solve real-world business problems at scale.Master's or Ph.D. in Computer Science/Engineering or other technical field.Exceptional interpersonal, technical, and communication skills as well as the ability to learn, evaluate, and adopt new technologies quickly.What Will Make You Stand Out (Preferred Qualifications) Experience in prompt engineering and fine-tuning Large Language Models (LLMs).Expertise in Graph Neural Networks/Knowledge Graphs and proficiency in unsupervised learning (clustering) and evaluation.Research experience/publications/patents in relevant areas of NLP and ML along with familiarity with public cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow, Airflow).
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