As a Sr. ML Engineer - Generative AI, you will build and deploy production-grade LLM systems for personalised learning in Indian languages. You will own RAG, agentic pipelines, evaluation, and backend services, with a solid focus on software engineering. The role offers high ownership in a 0-to-1 environment, requiring hands-on execution, adaptability, and comfort with ambiguity.

Key Responsibilities
Design, build, and ship production-grade LLM applications: RAG pipelines, agentic workflows, and tool-calling systems for education-specific use cases such as question answering, content generation, adaptive feedback, and curriculum alignment.
Own full system architecture: data pipelines, retrieval layers, orchestration, APIs, and service infrastructure written as maintainable, tested production code, not notebooks or scripts.
Build rigorous LLM evaluation frameworks: task-specific benchmarks, regression testing, human eval loops, and automated quality gates to catch degradation before it ships.
Own latency and cost at the application layer: caching strategies, request batching,



model/route selection, and prompt-context optimisation to keep production systems quick and affordable at scale.
Build data pipelines for grounding and instruction data, including multilingual and Indic language sources.
Assess new open-source and closed model releases for domain applicability, cost, and production readiness.
Define and track system performance metrics, evaluation benchmarks, and reliability targets across all shipped features.
Work with open-source and sovereign LLMs, integrating them into production-proven serving and orchestration frameworks.
Where warranted, fine-tune or adapt foundation models (LoRA/QLoRA/SFT)- a strong plus, not a gating requirement for this role.

Must-Have Skills
Robust production Python engineering: clean, tested, maintainable code - not scripts or notebooks. Comfortable owning services in production.
Hands-on experience building

📌 Senior Machine Learning Engineer Noida
🏢 The LHR Group
📍 Noida