Research Scientist

What You’ll Do

• Shape the future of agentic AI by pioneering new research directions in planning, reinforcement learning, multimodal reasoning, grounding, human-agent interaction, and alignment (e.g. reward modeling, automated task evaluation, AI safety).
• Design and execute experiments end-to-end: from data collection and benchmarking, to model training and evaluation.
• Develop new methodologies that push the boundaries of AI agent capabilities and reliabilities, advancing both academic and product impacts, in collaboration with world-class scientists and engineers.
• Collaborate closely with engineers to integrate research prototypes into product.
• Publish and present results at top-tier conferences, contributing to the broader AI research community.
• Advance the science hands-on through designing methods, building datasets, running experiments, and benchmarking against state of the art.

Qualifications

• PhD in Computer Science, Machine Learning, or related field, or equivalent research experience.
• Experience owning the complete research lifestyle: leading and executing a research program from ideation all the way to publication.
• Expertise in one or more of (but not limited to): Pre-training, post-training, or fine-tuning LLMs/VLMs, Reinforcement learning and/or LLM-based agents, Computer vision and multimodal learning, Representation learning and embeddings.
• Consistent publication record as first author in leading conferences (NeurIPS, ICML, CVPR, ACL, etc.).
• Strong implementation skills in modern ML frameworks (PyTorch, JAX, etc.).
• Demonstrated ability to run complex experiments, analyze results, and iterate quickly.
• Passion for high-impact research with real-world applications.
• Ambition and vision to redefine what’s possible in AI research and deployment.