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, Paris, Melbourne, Taipei, 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 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 .

About the role

Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience..

Within Netskope Engineering, the Netskope AI Labs is responsible for advancing state-of-the-art artificial intelligence (AI) and machine learning (ML) technology to power the Netskope Intelligent Security Service Edge (SSE) security platform. Leveraging our expertise in AI/ML and security, we are developing large-scale AI/ML solutions for SSE. For example, we are integrating the latest AI/ML technology into our data security and threat protection features, as well as business operations.

What's in it for you

We are looking for a talented and motivated machine learning scientist to join our team. A successful candidate has deep technical expertise in applying AI/ML technologies in security applications and/or adjacent domains, and must be passionate about cloud security. You will have the opportunity to work with a team of talented engineers, researchers, and machine learning engineers to solve the most challenging cloud security problems today.  

What you will be doing

• 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
• Develop 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
• Staying up-to-date with the latest developments in AI/ML such as large language models (LLM)

Required skills and experience

• Must have a true startup spirit and be willing to wear multiple hats and deliver end-to-end solutions
• 10+ (Sr. Staff) / 8+ (Staff) / 6+ (Senior) years of industry experience in developing AI/ML models, preferably on security products or services
• Hands-on experience with relevant technology stacks such as CUDA, Python, Tensorflow, LLM, etc
• Hands-on experience using modern big data pipelines and cloud computing platforms such as AWS, Azure, or GCP
• Natural language process (NLP) and data mining experience highly desirable
• Energetic self-starter with the desire to work in a dynamic fast-paced environment
• Excellent verbal and written communication skills and ability to explain complex concepts to non-technical stakeholders
• Ability to influence without authority

Education

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

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