ML Engineer - LLM Privacy
August 27
🏡 Remote – Anywhere in California
Description
• Own an ML privacy vertical e.g. data leakage attacks, sensitive PII detection, and/or membership inference attacks. • Collaborate with our engineering team to deliver real-world applications of your algorithms for our customers. • Generate high quality synthetic training data, train LLMs, and conduct rigorous evaluation and benchmarking.
Requirements
• Deep domain knowledge in privacy-preserving ML. • Practical experience in techniques to attack or defend ML models in terms of privacy. • Extensive experience in implementing multiple different types of LLM models and architectures in the real world. Comfortability with leading end-to-end projects. • Adaptability and flexibility. In both the academic and startup world, a new finding in the community may necessitate an abrupt shift in focus. You must be able to learn, implement, and extend state-of-the-art research. • Preferred: previous projects or research in LLM privacy.
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