Senior ML Security Engineer

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5 months old

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Build the future of data. Join the Snowflake team.

The Product Security team is responsible for securing the Snowflake product and platform, and ultimately protecting the company mission of mobilizing the world’s data. Machine learning is a major driver of Snowflake’s growth as our customers want to build and deploy ML models to turn their Snowflake data into powerful insights. Snowflake has made huge investments in ML and AI by building and acquiring new technology, and integrating first and third party ML models into the Snowflake ecosystem. Security is a fundamental requirement in order to win and maintain customer trust in this rapidly evolving technology ecosystem.

As a member of the Security Assurance team, you’ll be responsible for maintaining (and raising) the security bar across our suite of ML products. We are looking for a motivated, passionate expert in ML security who can help us build a world class security experience for our product development partners. Our security program focuses on shifting left, delegating autonomy to developers and automating critical tasks, and we need you to apply those same principles in the domain of ML product development.

Our ideal candidate wakes up each morning thinking about ways to scale security. Their goal is to lower risk while letting the business move quickly and safely. They believe security should be an inherent property of the tools and processes engineers and data scientists use every day. 


  • Take an active part and lead efforts in the team that designs, plans, and implements ML features and projects to integrate with and verify the security architecture of Snowflake
  • Lead with code, automation and data in everything you do: special focus is placed on frameworks, automation and tooling to increase ML engineer autonomy, detect security policy violations, and driving security outcomes through data consumption and enrichment
  • Work alongside ML engineering and security teams, providing expert leadership and advice on secure architecture, design, and implementation for machine learning solutions
  • Create and scale developer-friendly security products and tools
  • Create security impact across teams, with strong support from the business
  • Build a world class security experience for ML engineers, researchers and data scientists

Minimum Qualifications

  • Strong interest in the synthesis of machine learning and security engineering: you should be comfortable discussing threats that apply to machine learning (e.g. training data leakage, prompt injection, multi-tenancy workloads, membership inference, etc.)
  • Experience in reviewing design and implementation of multi-component software systems, especially those which are reliant on homegrown or third-party LLMs and APIs
  • Ability to automate tasks, collect, integrate and analyze data from multiple sources
  • Ability to design and write program/design specifications for self and others
  • Strong communicator who is comfortable working cross-functionally, with a track record of independence and delivering results
  • Able to work across team boundaries, reach consensus amongst disparate view points, and graciously receive feedback
  • Fluency in SQL

Preferred Qualifications

  • Familiarity with low-level GPU architecture
  • Data Science/ML Engineering background
  • Expert understanding of software security architecture and design, threat modeling, code review, SDLC best practices, and mitigations for common application security issues
  • Contributions to the security community, such as open source tools, research papers, conference talks, etc.