AI Research Scientist (Multi-agent Systems) | naptha.ai
About the role
We are seeking an exceptional AI Research Scientist to join Naptha AI at the ground floor, focusing on advancing the state of the art in multi-agent systems and agent interoperability. In this role, you will be responsible for researching and developing novel approaches to agent collaboration, coordination, and scalability. Working directly with our technical team, you will help shape the fundamental architecture of our agent interoperability platform.
This role is critical in solving core technical challenges around agent communication protocols, task delegation, and distributed intelligence. You will work at the intersection of multi-agent systems, machine learning, and distributed systems to develop practical solutions for real-world agent deployment and collaboration.
Core Responsibilities
Research & Development
Design and implement novel architectures for scalable multi-agent systems
Develop frameworks for agent communication and coordination
Research approaches to improve agent interoperability across different frameworks
Create efficient protocols for distributed task execution and resource management
Implement and test new ideas through rapid prototyping
Technical Innovation
Stay at the forefront of developments in multi-agent systems and AI research
Identify and solve key technical challenges in agent interoperability
Develop novel approaches to agent collaboration and task delegation
Bridge theoretical research with practical implementation
Contribute to the academic community through publications and open source
Platform Development
Help design and implement core platform architecture
Develop scalable solutions for agent deployment and management
Create tools and frameworks for agent monitoring and evaluation
Collaborate with engineering team on implementation
Build proofs of concept for new capabilities
Leadership & Collaboration
Work closely with engineering team to implement research findings
Mentor team members on advanced ML concepts and techniques
Contribute to technical strategy and roadmap
Collaborate with external research partners when appropriate
Help evaluate and integrate external research developments
In this role, you're a good fit if you have:
Strong background in machine learning and AI research
Deep understanding of multi-agent systems and reinforcement learning
Hands-on experience with modern agent frameworks (e.g., LangChain, AutoGPT)
Experience with ML infrastructure and deployment
Track record of implementing complex AI systems
Excellent programming skills (Python required, Rust a plus)
Strong analytical and problem-solving abilities
PhD in Machine Learning, Physics, Mathematics, or equivalent experience is a plus
Published research in relevant fields is a plus
Required Technical Experience:
Python programming and ML frameworks (PyTorch, TensorFlow)
Experience with agent frameworks (LangChain, AutoGPT, etc.)
MLOps and model deployment
Distributed systems and scalable architecture
Version control and collaborative development
Experience with large language models
About the hiring process:
Initial technical interview
Research presentation
System design discussion
Technical challenge
Team collaboration interview
Compensation & Benefits:
Competitive salary with significant equity stake
Remote-first work environment
Full medical, dental, and vision coverage
Flexible PTO policy
Learning and development budget
Conference and research publication support
Home office setup allowance
Additional Notes:
Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups
Strong bias for practical implementation of research ideas
Passion for advancing the field of multiagent systems
Interest in open source contribution and community engagement
Naptha AI is committed to building a diverse and inclusive workplace. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of background.