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
We are seeking a seasoned and highly experienced Staff Machine Learning Platform Engineer to join our team. As a member of our team, you will be responsible for leading the development and maintenance of our large-scale ML platform, ensuring data security, and driving innovation.
Responsibilities:
- Lead the design, development, and maintenance of the ML platform for processing large data sets at scale
- Collaborate with data scientists and engineers to integrate and deploy ML models into production with a focus on data security
- Build and implement secure data pipelines for processing sensitive data
- Develop and maintain monitoring, logging and alerting systems for ML models with a focus on data security and scalability
- Ensure high availability and scalability of the ML platform while maintaining data security standards
- Conduct performance tuning and optimization of ML models while considering data security implications
- Mentor and guide junior team members on ML platform development and best practices
- Contribute to development and maintenance of software engineering best practices, standards, and tools with a focus on data security
Qualifications
- BS/MS in Computer Science, or a related field
- 8+ years of experience in building and deploying large-scale ML platforms, with industrial experience such as Uber's Michelangelo or Meta's Pytorch
- Strong experience in Python, and related data science libraries (numpy, pandas, scikit-learn, etc.)
- Expertise in cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) with a focus on data security
- In-depth knowledge of database systems (SQL and NoSQL)
- Strong understanding of distributed computing frameworks (Hadoop, Spark, etc.)
- In-depth knowledge of data security best practices
- Excellent communication and collaboration skills, able to lead cross-functional teams and prioritize data security
- Experience with various program languages such as Go, desired.
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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.
