Machine Learning Lead

At Nurix AI, we are pioneering the Autopilot Enterprise. Our conversational AI agents handle workflows, drive outcomes, and deliver measurable impact for businesses. Born from the belief that enterprises need a new playbook, we build autonomous, multilingual agents capable of complex reasoning, contextual understanding, and end-to-end workflow ownership. Backed by $27.5M in funding from Accel, General Catalyst, and Meraki Labs, and led by Mukesh Bansal, we are India's first scaled enterprise AI company, delivering cutting-edge AI solutions that integrate seamlessly into workflows across industries like Retail, Insurance, Education & Home Services. Join us in shaping the future of enterprise AI - where every interaction is smarter, faster, and human-like.

We are seeking an experienced and visionary Engineering Lead - ML to spearhead the development of next-generation conversational and dynamic AI agents. You will architect and scale systems that enable:

Conversational Agents (Voice & Chat): Human-like, open-ended dialogues without rigid workflow design. Dynamic reasoning to achieve goals (e.g., selling a personal loan). Continuous self-learning from conversation outcomes. Operating at minimal latency and cost. Dynamic Workflow Agents: Agents that learn workflows (Sales, Support, Admin) by observing humans. Self-learning from live agent behavior, recordings, and transcripts. Ability to see, process/understand, reason, and interact with GUIs/browsers. One-shot learning from escalations, ensuring accurate human-AI collaboration. Human agent assist & copilot features driven by workflow context. This is a rare opportunity to shape how enterprises adopt agentic AI, working directly at the intersection of AI research, applied ML, scalable infrastructure, and real-world enterprise workflows.

6-10 years of experience. Strong expertise in Reinforcement Learning, Computer Vision, LLM fine-tuning, and applied ML research. Proven ability to build and scale large-scale distributed systems and enterprise-grade products. Deep understanding of cloud platforms (AWS, GCP, Azure) and scalable architecture. Proficiency in Python, Go, Java, or equivalent languages. Passion for building product-first AI systems (not services), strong execution ability, and innovation-driven leadership.