Harmony is building a new AI venture inside monday.com to redefine how businesses interact with their customers through next-generation conversational AI and agentic systems. Our AI doesn’t just react - it plans, reasons, and acts.
You’ll join a small, highly autonomous team with the agility, ownership, and pace of a startup, working alongside world-class engineers and researchers to build the next generation of conversational AI. You’ll have access to large-scale real-world data, the compute and resources to pursue groundbreaking research, and the freedom to move fast while helping shape Harmony’s AI vision.
About The Role
• Research novel algorithms and design new deep learning architectures to advance our in-house NLP and conversational models.
- Develop methods for translating customer goals into structured representations with controlled states and real-time observations.
- Help design the reasoning layer that orchestrates our AI models efficiently alongside a range of LLMs, enabling each agent to adapt its policy throughout a conversation while remaining aligned with customer objectives.
- Build analytical tools that trace our AI decision process across a vast corpus of conversations, providing clear visibility into their reasoning and behavior.
- Collaborate closely with engineers and product teams to translate cutting-edge research into production at scale.
- Proactively lead new ideas and technical initiatives.
Requirements
• MSc or PhD in Computer Science, Mathematics, Physics, Electrical Engineering, or a closely related field.
- Proficiency in Python.
- Strong theoretical background in machine learning and deep learning principles.
- Solid understanding of NLP concepts and relevant linguistic principles (co-reference, natural language inference, grammatical relations, and similar).
- Experience using statistics and information theory to evaluate AI models and conduct EDA.
- 4+ years of experience conducting NLP research with deep learning models and frameworks (PyTorch, TensorFlow, and similar).
- Experience shipping AI systems from research to production.
- Experience with conversational AI agents is a big plus.
- Publications at top-tier conferences (ACL, EMNLP, NeurIPS, ICML, CVPR) are a plus.