ML Research Engineer - LLM Safety

August 27, 2024

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⏰ Full Time

🟡 Mid-level

🟠 Senior

📚 Research Engineer

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Dynamo AI

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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.

11 - 50 employees

🤖 Artificial Intelligence

📋 Compliance

🔐 Security

💰 $15.1M Series A on 2023-08

📋 Description

• Own an LLM vertical with a focus on a specific safety domain, technique, or use case (either from defense or red-team attack perspective) • Generate high quality synthetic data, train LLMs, and conduct rigorous benchmarking. • Deliver robust, scalable, and reproducible production code. • Push the envelope by developing novel techniques and research that delivers the world’s most harmless and helpful models. Your research will directly empower our customers to more feasibly deploy safe and responsible LLMs. • Co-author papers, patents, and presentations with our research team by integrating other members’ work with your vertical.

🎯 Requirements

• Deep domain knowledge in LLM safety techniques. • Extensive experience in designing, training, and 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: past research or projects in either attacking or defending LLMs.