Member of Technical Staff/Staff Engineer(Machine Learning Scientist)

Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. 

Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Melbourne, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events (pre and hopefully post-Covid) and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive.  Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope.

Machine Learning Scientist

Within Netskope Engineering, the Security Services organization is responsible for building core security products and features such as Data Loss Prevention, Malware and Threat Prevention, and Cloud Confidence Index, Breach, and Anomaly Detection by applying Artificial Intelligence and Machine Learning technologies across the Netskope cloud security platform. We are looking for talented machine learning scientists with security domain knowledge. A successful candidate has deep technical expertise in applying AI/ML technologies in security applications and/or adjacent domains, ideally has been through the entire lifecycle of an award winning security product, and must be passionate about cloud security. You will have the opportunity to work with a team of talented engineers, researchers, and machine learning scientists to solve the most challenging cloud security problems today.   

Responsibilities:

• Identify strong AI/ML use cases in cloud security, data security, and adjacent domains, leveraging Netskope’s rich set of data sources
• Define scalable data acquisition and labeling strategy for specific use cases
• Work with data engineers to retrieve, clean, and normalize data and ensure a scalable and continuous high-quality data stream
• Work closely with threat research and development teams in feature engineering, making sure high-quality feature sets are chosen in a systematic way
• Select ML models for defined use cases and implement KPIs to ensure optimal algorithms and results
• Conduct strict internal testing to ensure high efficacy, low false positive and false negative rate
• Interpret results and communicate findings
• Document use case, data acquisition, feature engineering, training, validation, deployment, future improvement opportunity, and other important aspects
• Work closely with development and QE teams in productization
• Be an evangelist of AI/ML within Netskope and promote AI/ML wherever applicable, beyond security use cases
• Collaborate with the data analytics team to define new platform requirements and continuously improve our horizontally scalable data lake

Qualifications/Requirements:

• Must have a true startup spirit and be willing to wear multiple hats and deliver end-to-end
• Ability to think outside the box and evaluate results based on customer value
• 5+ years of industry experience in applying AI/ML, preferably on well-known security products or services, such as malware detection, anomaly detection, security analytics, and data security
• Experience applying AI/ML in more than one domain highly desirable
• Hands-on experience with relevant technology stacks such as CUDA, Python, R, Spark, Flink, or Tensorflow
• Hands-on experience using modern big data pipelines
• Natural language process (NLP) and data mining experience highly desirable
• Security research experience and strong security domain knowledge highly desirable
• Energetic self-starter with the desire to work in a dynamic fast-paced environment
• Excellent verbal and written communication skills
• Ability to influence without authority

Education:

• Advanced degree in Computer Science, Statistics, Electrical Engineering, or equivalent technical degree

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