Research Scientist (Multi-agent Systems)

ZipRecruiter; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

ZipRecruiter is looking for an AI Research Scientist to join Naptha AI, aiming to advance multi-agent systems and agent interoperability. In this role, you'll research and develop innovative solutions, addressing core technical challenges and enhancing collaboration between agents in real-world applications.

Benefits

Competitive salary with 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

Qualifications

• Strong background in machine learning and AI research.
• Experience with ML infrastructure and deployment.
• Published research in relevant fields is a plus.

Responsibilities

• Design and implement novel architectures for scalable multi-agent systems.
• Collaborate with engineering team to implement research findings.
• Develop frameworks for agent communication and coordination.

Skills

Machine Learning

AI Research

Agent Collaboration

Problem Solving

Programming

Analytical Skills

Education

PhD in Machine Learning, Physics, or Mathematics

Tools

Python

PyTorch

TensorFlow

Agent Frameworks (LangChain, AutoGPT)

Job description

Job DescriptionJob DescriptionAI 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 ResponsibilitiesResearch & 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 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.