ML Engineer — LLM Privacy

A CB Insights Top 100 AI Startup focused on developing LLMs with safety, privacy, and real-world responsibility.
Machine Learning
Senior Software Engineer
Remote
51 - 100 Employees
5+ years of experience
AI

Description For ML Engineer — LLM Privacy

Dynamo AI is at the forefront of developing LLMs with a focus on safety, privacy, and real-world responsibility. As a 2023 CB Insights Top 100 AI Startup, they're building the premier platform for private and personalized LLMs, working with Fortune 500 companies to implement frontier research in their next-generation LLM products.

The ML Engineer role focuses on LLM Privacy, where you'll work with a team of ML Ph.D.'s and builders in a fast-paced environment free from traditional bureaucratic constraints. You'll be responsible for owning an ML privacy vertical, working on cutting-edge challenges like data leakage attacks, sensitive PII detection, and membership inference attacks.

The ideal candidate will bring deep expertise in privacy-preserving ML and practical experience with LLM implementations. You'll be working in an environment that values quick iteration and real-world impact, seeing your work affect end customers in weeks rather than years. The role offers the opportunity to contribute to the democratization of safe and responsible AI while maintaining a strong focus on user privacy.

The position requires someone who can adapt quickly to new research findings and implement state-of-the-art solutions. You'll be part of a team that's committed to building fair, unbiased, and responsible LLMs, challenging the status quo that often sacrifices user privacy for ML advancement. This is an excellent opportunity for someone passionate about both the technical challenges of ML privacy and the practical implementation of these solutions in real-world applications.

Last updated 20 days ago

Responsibilities For ML Engineer — LLM Privacy

  • Own an ML privacy vertical e.g. data leakage attacks, sensitive PII detection, and/or membership inference attacks
  • Collaborate with engineering team to deliver real-world applications of algorithms for customers
  • Generate high quality synthetic training data, train LLMs, and conduct rigorous evaluation and benchmarking

Requirements For ML Engineer — LLM Privacy

Python
  • 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
  • Adaptability and flexibility to learn, implement, and extend state-of-the-art research
  • Preferred: previous projects or research in LLM privacy

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