Senior ML Engineer, AI Security
Description
Key Responsibilities
Example projects
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Extend the scope of one of our detectors to support multiple languages without dropping performance on already supported languages.
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Increase the scope where our defenses perform by 100x (e.g., multi-lingual data, code, etc).
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Extend modeling and data generation to enable passing additional context to our prompt injection detectors, such as the LLM output and behavioral metadata.
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Red team our model to understand the most pressing vulnerabilities of our detectors and prioritize the data collection and generation required to fix them.
Qualifications
What you’ll bring
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You have at least 4 years of experience shipping machine learning models to production, ideally in environments where reliability and quality are key (e.g., autonomous driving, industrial applications, healthcare).
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Most of your experience productionizing ML models has been in unstructured data spaces such as NLP and vision.
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You have had experience working on end-to-end development of ML models.
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You have experience working on the “long tail” of data distribution, bringing models from prototypes to real-world systems.
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You aspire to play a pivotal role in defining the future of secure AI within a mission-driven company with ambitious goals.