AI Research Engineer
About Alaris
Alaris Security is building the core technology stack for intelligent cyber security. Designed for enterprise and defense organizations, our platform unifies security data through our proprietary graph database and automates critical tasks using our agent framework. Together these technologies allow us to provide a suite of products that enhance defensive cyber security operations, including automating critical use-cases: alert analysis, vulnerability triage, investigations, incident response, and attack staging detection among many others.
About the Role
As an AI Research Engineer, you will apply cutting edge research techniques to improve the autonomy and effectiveness of our security agents. This job involves both full stack development — building new agents and improving our agent frameworks — along with novel research — applying techniques like reinforcement learning in the cyber domain. In this position you will closely follow emerging AI research and ideate on interesting applications of that research. As an early member of the team you will play a key role in shaping our research program.
What you'll do
- Build new AI agents for security use-cases.
- Refine existing agents to improve performance.
- Design an evaluation system for calculating performance metrics for our agents.
- Implement cutting edge reinforcement learning algorithms for improving agent performance, long term autonomy, and reducing the specialization of agents to specific tasks.
- Identify promising new research and lead programs for testing and ultimately implementing that research.
- Contribute where necessary across our software stack.
Requirements
- Strong research experience, demonstrated through personal projects or job experience
- 1+ years of software engineering experience in a production environment
- Experience with Python, PyTorch, TypeScript, building AI agents
- Strong theoretical understanding of language models
- Understand reinforcement learning (preferred)
- Be excited about working for an early stage fast paced startup and putting in 60+ hour weeks