Dynamo AI
Dynamo AI is a company that specializes in providing end-to-end privacy, security, and compliance solutions for enterprises adopting AI technologies. Their product suite covers the entire AI development lifecycle, offering tools like DynamoEval for automated stress testing, DynamoEnhance for risk remediation and model enhancement, and DynamoGuard for deploying AI guardrails and auditing LLM usage. Dynamo AI prepares organizations for emerging AI regulations by automating vulnerability assessments and bolstering red-teaming processes, ensuring compliance with regulatory changes such as the EU AI Act. The company aims to help enterprises manage the security and privacy challenges posed by AI adoption.
ML Engineer - LLM Privacy
August 27, 2024
Dynamo AI
Dynamo AI is a company that specializes in providing end-to-end privacy, security, and compliance solutions for enterprises adopting AI technologies. Their product suite covers the entire AI development lifecycle, offering tools like DynamoEval for automated stress testing, DynamoEnhance for risk remediation and model enhancement, and DynamoGuard for deploying AI guardrails and auditing LLM usage. Dynamo AI prepares organizations for emerging AI regulations by automating vulnerability assessments and bolstering red-teaming processes, ensuring compliance with regulatory changes such as the EU AI Act. The company aims to help enterprises manage the security and privacy challenges posed by AI adoption.
📋 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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