DepthFirst-posted 3 months ago
Full-time • Mid Level

We’re seeking an experienced Research Engineer to join our effort in building and training AI agents for vulnerability discovery and exploitation. We are building a technology capable of finding the next Log4J at scale, finding and remediating vulnerabilities in customer and open source codebases. We are looking for strong engineers with strong intuition, experience in model evaluation and benchmarks. Reinforcement Learning experience is a plus. Your work will play a crucial role in building a product that aims to redefine how companies do security.

  • Build State-of-the-Art AI Agentic pipelines optimized for discovering intricate software vulnerabilities and generate exploits
  • Design, Maintain and Evolve evaluation benchmarks for AI agents that reflects the problems our users face
  • Design & Develop training procedures and reinforcement learning environments to train security coding agents
  • Work on a Product that Solves a Critical Problem - and we already have a handful of customers who have found it valuable in fixing some eye-opening vulnerabilities within the first few days of using our product.
  • 3+ years of full-time experience in AI research engineering in machine learning, deep learning, and/or natural language processing
  • Experience with developing machine learning models at scale from inception to business impact
  • Programming experience in Python and hands-on experience with frameworks such as PyTorch
  • A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience
  • A love for technology, and an insatiable curiosity for new tools to tackle real problems
  • Capable of solving complex problems with simple solutions. Building reliable and scalable products, making right trade-offs along the way
  • A tendency to leave things in a better way than you found it
  • Reinforcement Learning experience is a plus
  • Competitive Salary with generous equity
  • Health and Dental Insurance
  • Office lunch (when working from our San Francisco office)
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