AI Researcher

At Emergence, we’re pioneering a self-improving intelligent agent designed to revolutionize human-machine collaboration. Our “orchestrator” increases the reliability and accuracy of AI models while reducing costs and processing times. Our team has created award-winning systems currently utilized in hundreds of settings across the United States.
Currently ~140 employees strong, our remote-first team is spread across 10 countries and quickly expanding. We also have offices in New York City, Southern California and India. If you’re passionate about AI and ready to help shape the future of multi-agent systems, we’d love to hear from you!
We're looking for full time AI researchers in the area of multi-agent systems, who will work with us either remotely or on-site at our NYC headquarters. AI Researchers will collaborate closely with our larger team on designing, developing and deploying real-world AI systems, from creating new models, algorithms and systems, to optimized deployment on multi-GPU systems at scale.
The ideal candidate would have a Ph.D. in AI/ML/CS or related technical field, with a strong background in multi-agent systems and decision-making using foundation models. If you have research or industry experience and are passionate about applying bleeding edge AI to real-world problems, we'd love to hear from you.

What You’ll Do

• Multi-agent and tool-using systems
• Sequential decision-making using language models including multi-step
• Reasoning and planning, and related training methods
• Continuous learning and self-learning
• Neuro-symbolic reasoning
• Contextual bandits, reinforcement learning and reward modeling
• Experience with classical planning techniques and AI agent frameworks is a plus
• Experience with large foundation models, including hands-on familiarity with different training modalities (CPT/DPT, SFT, instruction-tuning, alignment, ...) is a plus

Preferred Qualifications

• Graduate degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field (PhD students preferred)
• 5+ years of research or industry experience in one of the areas listed above
• Publications at strong AI/NLP conferences (Neurips, ICLR, ICML, ACL, NAACL, EMNLP, ...)
• Expertise in deep-learning frameworks including one or more of PyTorch, TensorFlow, Jax