Position: Staff Software Engineer (Machine Learning Platform)
Location: San Jose, CA
Zscaler is the world's largest inline security cloud company. It is also one of the fastest-growing SaaS companies on the planet and a once-in-a-generation software company. Zscaler secures more than 150 billion transactions per day, protecting thousands of customers (including 25% of Global 2000) from cyberattacks and data loss. The sheer volume of data Zscaler processes is astronomical to comprehend: Zscaler ZIA transactions per day are 150 billion while Google searches per day are “only” 5.7 billion.

We work in a fast-paced, dynamic, and make it happen culture. Our people are some of the brightest and passionate in the industry. They thrive on being the first and best to solve problems. Just within a year, the ML team members have filed more than ten (10) patents. We are always looking to hire highly passionate, collaborative, and humble people that want to make a difference.
Responsibilities:

As a Staff Software Engineer, you will work in an award-winning team that does full-lifecycle full-stack Machine Learning platform development.

• You will be working with the massive scale of network data, security data, and enterprise data every day. 

• You need to have a passion for building out tools and platforms, processing and analyzing data at scale, and solving real-world business problems.

• You may not have prior data science and ML background but need to build up knowledge in this area and tremendous curiosity in how the data can and will be utilized by the data scientist. 

• As a backend software engineer within our Machine Learning platform, your primary responsibilities include the following:
• You will help build large-scale distributed systems to support the Machine Learning pipeline, including data collection, feature engineering, model training, model evaluation, model deployment, and real-time service. 
• You will apply analytical and math/statistics skills to stay on top of data and to ensure results are coherent and reliable.
• You will solve complex real-world business problems (e.g., threat detection, automation, and business intelligence) by working closely with various stakeholders including data scientists, product management, and product engineering teams.

Required Skills:

• Degree in Computer Science, Machine Learning, or Electrical Engineering from a reputed university (Master/PhD preferred but not required)
• Very strong algorithm, data structure, computer science foundation 
• 5+ years of industry experiences in software engineering, building quality software by writing robust interfaces, considering design principles, and applying sound testing practices
• 3+ years of industry experiences in Python and SQL
• 3+ years of industry experience using distributed data processing such as Spark, BigQuery, or Apache Beam
• 3+ years of industry experience with various cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow). 
• 3+ years of industry experience with Docker, Kubernetes, and event messaging such as Kafka, RabbitMQ, etc
• Excellent understanding of operating systems and distributed systems.
• Excellent interpersonal, technical, and communication skills
• Very good business sense.
• Ability to learn, evaluate, and adopt new technologies fast

Desirable Skills:

• Experience with Go, C++, or Javascript
• Experience with setting up SQL/NoSQL database such as Postgres, MongoDB, Redis, and table schema
• Experience with machine learning or deep learning related toolset/frameworks, such as Pandas, Numpy, Scikit-learn, TensorFlow, PyTorch, etc.
• Familiarity with networking and networking security

Why Zscaler?

People who excel at Zscaler are smart, motivated and share our values. Ask yourself: Do you want to team with the best talent in the industry? Do you want to work on disruptive technology? Do you thrive in a fluid work environment? Do you appreciate a company culture that enables individual and group success and celebrates achievement? If you said yes, we’d love to talk to you about joining our award-winning team.

Learn more at zscaler.com or follow us on Twitter @zscaler. Additional information about Zscaler (NASDAQ : ZS ) is available at http://www.zscaler.com. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.
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