Design and implement safety architectures for Agentic AI systems, including guardrails, reward modeling, and self-monitoring capabilities
Lead and collaborate on alignment techniques such as inverse reinforcement learning, preference learning, interpretability tools, and human-in-the-loop evaluation
Develop continuous monitoring strategies for agent behavior in both simulated and real-world environments
Partner with product, legal, Responsible AI, governance, and deployment teams to ensure responsible scaling and deployment
Contribute to and publish novel research on alignment of LLM-based agents, multi-agent cooperation/conflict, or value learning
Proactively identify and mitigate failure modes, e.g., goal misgeneralization, deceptive behavior, unintended instrumental actions
Set safety milestones for autonomous capabilities as part of deployment readiness reviews

Master's Degree and 4+ years of experience in research/ML engineering or an applied research scientist position preferably with a focus on developing production-ready AI solutions
2+ years of experience leading development of AI/ML systems
Deep expertise in AI alignment, multi-agent systems, or reinforcement learning
Demonstrated ability to lead research-to-production initiatives or technical governance frameworks
Strong publication or contribution record in AI safety, interoperability, or algorithm ethics

Lead Data Scientist – Safety Alignment

Key skills