
Building Advanced AI Systems
5 days ago
About the Position
We are seeking a highly skilled Applied AI Researcher to join our innovative research team. This role will focus on advancing AI capabilities through rigorous experimentation, multi-agent systems design, domain-specific scaffolding, and evaluation methodology development.
- Develop novel multi-agent architectures for complex problem-solving and collaboration
- Design domain-specific scaffolding techniques to guide AI systems in specialized environments
- Create high-quality datasets for training and evaluating AI systems across domains
- Establish comprehensive evaluation frameworks to measure system performance, robustness, and alignment
- Research and implement reinforcement learning approaches for agent behavior optimization
- Develop techniques for post-training optimization and domain adaptation
- Collaborate with cross-functional teams to translate research findings into practical applications
- Stay current with AI advancements and contribute to the research community
- Document methodologies, findings, and best practices for internal knowledge sharing
Key Qualifications:
- Advanced degree in Computer Science, Machine Learning, or related field
- 4+ years of experience in applied AI research
- Strong mathematical foundations in optimization, probability theory, and linear algebra
- Extensive expertise in Python programming and software development
- Strong proficiency in PyTorch or JAX for implementing and scaling AI models
Preferred Experience:
- Publishing record in top-tier AI/ML conferences
- Experience applying AI to scientific domains such as drug discovery, materials science, chip design, or mathematical reasoning
- Experience working with vision-language models and multimodal architectures
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