Senior Machine Learning Engineer - NLP

Observe.AI
BengaluruPosted 6 March 2026

Job Description

<p><strong>About Us</strong></p> <p><a href="http://observe.ai/">Observe.AI</a> is the enterprise-grade Customer Experience AI platform that unifies conversations, intelligence, and action to turn contact centers into performance engines. Built to optimize the full lifecycle of human and AI agents, <a href="http://observe.ai/">Observe.AI</a> enables enterprises to automate customer interactions, augment agent performance, and deliver governed AI at scale.</p> <p>On a single platform, <a href="http://observe.ai/">Observe.AI</a> combines Voice and Chat AI Agents, real-time AI Copilots, and Conversation Intelligence with 100% interaction coverage for quality, compliance, and performance management. Trusted by brands like DoorDash, Affordable Care, Signify Health, and Verida, <a href="http://observe.ai/">Observe.AI</a> delivers fast time-to-value, measurable ROI, and consistent, high-quality customer experiences across every channel.</p> <p><strong>Why Join Us</strong></p> <p>At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers. </p> <p>If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy. </p> <p>Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries.</p> <p><strong>What you’ll be doing</strong></p> <ul> <li>Design develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment.</li> <li>Work with cutting-edge tools and technologies in Machine Learning, Deep Learning Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI.</li> <li>Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform.</li> <li>Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.</li> <li>Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders.</li> <li>Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.</li> <li>Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform.</li> <li>Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc.</li> </ul> <p><strong>What you’ll bring to the role</strong></p> <ul> <li>Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU.</li> <li>An engineering mindset with the competencies of an applied scientist. </li> <li>3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems.</li> <li>Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications.</li> <li>Good understanding of recent advances in building LLM-powered ... (truncated, view full listing at source)