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Staff Software Engineer (Machine Learning Platform)

Zscaler

Staff Software Engineer (Machine Learning Platform)

San Jose, CA
Full Time
Paid
  • Responsibilities

    Job Description

    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.
  • Qualifications

    Qualifications

    • 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

    Additional Information

    All your information will be kept confidential according to EEO guidelines.

     

    #LI-JM1

    WHAT YOU CAN EXPECT FROM US:

    • An environment where you will be working on cutting edge technologies and architectures
    • A fun, passionate and collaborative workplace
    • Competitive salary and benefits, including equity

    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.  Additional information about Zscaler (NASDAQ: ZS ) is available at https://www.zscaler.com. 

    Zscaler is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

  • Industry
    Executive Office