Senior Machine Learning Engineer
TAAS Partners
2 - 8 years
Bengaluru
Posted: 21/02/2026
Job Description
About Client - 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.
Role Overview
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.
Key Responsibilities
Leadership & Vision
- Lead and mentor a team of engineers building agentic AI systems.
- Define technical vision, architecture, and product strategy.
Architecture & Delivery
- Design and scale enterprise-grade AI products leveraging reinforcement learning, computer vision, and LLM fine-tuning.
- Drive low-latency, cost-optimized systems in production.
- Ensure robust engineering standards, testing, and security practices.
Innovation & Integration
- Develop pipelines for self-learning agents from conversations and human workflows.
- Architect systems for human-in-the-loop escalation and AI copilots.
- Collaborate with product, design, and research teams to deliver real-world outcomes.
Operational Excellence
- Establish CI/CD pipelines, automation, and best practices.
- Proactively identify risks and resolve technical challenges.
- Optimize for scalability, reliability, and enterprise integration.
What Were Looking For
- Experience: 2-8 years of experience.
- AI/ML Skills: Strong expertise in Reinforcement Learning, Computer Vision, LLM fine-tuning, and applied ML research.
- Systems Expertise: Proven ability to build and scale large-scale distributed systems and enterprise-grade products.
- Infrastructure Skills: Deep understanding of cloud platforms (AWS, GCP, Azure) and scalable architecture.
- Hands-on Engineering: Proficiency in Python, Go, Java, or equivalent languages.
- Mindset: Passion for building product-first AI systems (not services), strong execution ability, and innovation-driven leadership.
Why Join?
- Work at the cutting edge of AI and enterprise technology
- Be part of a mission-driven, high-growth startup
- Direct impact on products used by large-scale enterprise clients
- A vibrant and dynamic work environment fostering professional growth and innovation.
- Competitive compensation and performance-based incentives.
- A front-row seat in the GenAI revolution, working with a team of passionate, like-minded innovators.
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