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Cutting-Edge AI Researcher
3 weeks ago
We are seeking a highly skilled Research Scientist to join our innovative team focused on developing cutting-edge solutions at the intersection of Artificial Intelligence (AI) and Quantum Computing. The successful candidate will contribute to advancing AI capabilities through rigorous experimentation, multi-agent systems design, domain-specific scaffolding, and evaluation methodology development.
This role offers an exciting opportunity to develop Compound AI systems impacting areas like Drug Discovery, Decision Intelligence, Chip Design, and Quantum Computing. Our team works in a collaborative environment with top researchers and engineers to drive progress by developing groundbreaking solutions to complex industry challenges.
Key Responsibilities- Design and implement novel multi-agent architectures that enable complex problem-solving and collaboration
- Develop domain-specific scaffolding techniques to guide AI systems in specialized environments
- Create and curate high-quality datasets for training and evaluating AI systems across various 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 the latest advancements in AI research and contribute to the research community
- Document methodologies, findings, and best practices for internal knowledge sharing
The ideal candidate will possess a strong foundation in Computer Science, Machine Learning, or related technical fields, accompanied by 4+ years of experience in applied AI research. Key qualifications include:
- Advanced degree (MS or PhD)
- 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
- Demonstrated experience with various reinforcement learning post-training methods (RLHF, DPO, GRPO, SFT, etc.)
- Experience working with vision-language models and multimodal architectures
- Knowledge of distributed training on multi-node, multi-GPU clusters
- Experience with dataset curation, cleaning, and augmentation for diverse AI tasks
- Strong understanding of model evaluation metrics and methodology development
- Opportunity to work on cutting-edge AI research with real-world impact
- Access to substantial computational resources for large-scale experimentation
- Collaborative environment with top researchers and engineers
- Flexibility to pursue novel research directions within the company's mission
- Competitive compensation and benefits package
