About Zscaler
Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company’s cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances.
Zscaler was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. Zscaler’s purpose-built security platform puts a company’s defenses and controls where the connections occur—the internet—so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside.
Job Description
Our team’s use cases include but are not limited to threat detection, policy recommendation, LLM-powered applications, malware detection, content classification, anomaly detection, and AIOps (advanced networking diagnosis). These various use cases give you the opportunity and challenges to experience multiple machine learning algorithms and tools.
You will design and create machine learning models to provide faster and more effective ways to address cloud security, cloud operations, and cloud intelligence use cases.
You might not be an expert in every stage of a Machine Learning project, but you should have interests and curiosity in various parts ranging from the data to the model’s business impact.
Qualifications
- 4+ years of experience as a Machine Learning Engineer or Data Scientist
- Experience with Python (pandas, sklearn, pytorch) and SQL
- Experience with feature engineering, model evaluation and model error analysis
- Experience with Large Language Models (LLMs)
- Master's Degree in Computer Science/Engineering required, data science concentration is a plus; PhD is preferred
- Passion for leveraging ML/AI to solve real-world business problems (better security and better business results)
- Excellent interpersonal, technical, and communication skills
- Good business sense and customer obsession
- Ability to learn, evaluate, and adopt new technologies fast
- Ability to lead and execute projects from start to finish
- Solid computer science foundation
Additional Preferred Skills
- Prompt engineering and fine tuning Large Language Models (LLMs)
- Graph Neural Networks/Knowledge Graphs
- Experience with unsupervised learning (clustering), and evaluating unsupervised models
- Experience with active/few-shot learning
- Experience with logs analysis/logs mining
- Research Experience/Publications
- Experience with various public cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow).
- Experience with various program languages such as (Py)Spark.
- Good understanding of operating systems and distributed systems.
- Familiarity with networking and networking security .
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By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.
Zscaler is proud to be an equal opportunity and affirmative action employer. We celebrate diversity and are committed to creating an inclusive environment for all of our employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status or any other characteristics protected by federal, state, or local laws.
See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.
Pay Transparency
Zscaler complies with all applicable federal, state, and local pay transparency rules. For additional information about the federal requirements, click here.
Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.
