About the job:- Design and develop next-generation AI agents powered by large language models, enabling autonomous reasoning, planning, and task execution.
- Build core agent capabilities such as memory, tool use, self-reflection, and long-horizon decision-making.
- Develop and optimize multi-agent systems to support collaboration, coordination, and complex problem solving.
- Integrate AI agents with external tools, APIs, and real-world systems to enable end-to-end automation.
- Explore and advance techniques in reasoning-enhanced LLMs, agent alignment, and embodied intelligence.
- Collaborate with cross-functional teams to translate cutting-edge research into scalable, production-ready systems.
The
total target annual compensation for this position ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.
About the ideal candidate:- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent industry experience.
- Strong background in large language models, AI agents, or decision-making systems.
- Track record of research contributions, including publications in venues such as NeurIPS, ICML, ICLR, or equivalent applied work.
- Experience rapidly turning ideas into working prototypes and experiments.
- Solid engineering skills (e.g., Python, PyTorch) and experience working with large-scale ML systems.
- Familiarity with agent architectures (e.g., tool use, retrieval, planning, memory) is highly preferred.
- Strong communication skills and the ability to work across research, engineering, and product teams.
