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About us: ConveGenius is an AI-native education infrastructure company transforming how governments, enterprises, and social institutions deliver learning and governance outcomes at population scale. Operating across B2G and B2B segments, the company partners with state governments, CSR funders, philanthropies, and social enterprises to build intelligent education ecosystems that are both impactful and commercially sustainable. At its core, ConveGenius runs two synergistic business lines: SwiftAI – the intelligence and automation layer that powers citizen engagement, governance efficiency, and real-time decision-making for governments and institutions. SwiftSchool – the learning infrastructure layer that integrates adaptive learning, digital classrooms, and analytics to drive measurable student and system outcomes. This dual-engine model enables ConveGenius to serve as the technology backbone for education reform — connecting classrooms, communities, and command centres through a unified AI-powered framework. Unlike traditional edtech companies that deliver content, ConveGenius builds infrastructure — platforms that integrate deeply into public delivery systems while enabling private and philanthropic partners to scale their missions with measurable results. With operations across 22+ Indian states and partnerships with multilaterals, CSR alliances, and government departments, ConveGenius has established itself as a partner-friendly enterprise trusted for aligning policy priorities with social and financial returns. Supported by institutional investors and guided by a double bottom line philosophy, the company consistently delivers impact at scale and profitability with purpose. As ConveGenius enters its next phase of growth, it is shaping the future of AI-led public education infrastructure — where technology, partnerships, and governance intelligence converge to redefine how nations learn and thrive. Learn more about us: https://linktr.ee/convegenius11 As the ML Engineer at ConveGenius, you will design, build, and ship production LLM-powered systems that power personalised learning in Indian languages and educational contexts. You own applications end-to-end: RAG and agentic pipelines, evaluation harnesses, and the services that serve them in production — with a strong bar for software engineering, not just model or prompt work. Fine-tuning experience is a plus for this role, not a requirement. 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 fast 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 Strong production Python engineering: clean, tested, maintainable code — not scripts or notebooks. Comfortable owning services in production. Hands-on experience building and shipping RAG or agentic systems in production: retrieval design, orchestration (e.g. LangChain/LangGraph or equivalent), tool calling, and multi-step reasoning pipelines. Demonstrated experience building LLM evaluation systems: benchmarks, regression tests, human-eval workflows, and quality monitoring — not just anecdotal "it works." Experience building and operating backend systems/services: APIs, data pipelines, deployment, and monitoring in a real production environment. Working knowledge of AI/ML pipelines, data preparation, and model deployment. Experience working with open-source and sovereign LLMs, using standard, production-proven frameworks. Understanding of cloud platforms and infrastructure for serving ML/LLM systems at scale. Good to Have Hands-on fine-tuning experience with LoRA, QLoRA, SFT, DPO, or similar preference-optimisation techniques. Familiarity with DeepSpeed, FSDP, or large-scale distributed training frameworks. Experience with inference optimisation (quantisation, ONNX, efficient serving) at the model layer What We Offer and Why You Should Join ConveGenius At ConveGenius, we create an environment where purpose meets growth. You will be part of a mission driven organization that is transforming how learning reaches children across India, especially at scale and where it matters most. Work with a diverse and passionate team spread across India, bringing together people from different backgrounds, perspectives, and expertise. Be part of an organization with a strong on ground presence across more than two thirds of India, giving you exposure to large scale, real world impact. Play a meaningful role in strengthening the education ecosystem and contributing directly to learning outcomes for millions of children. Gain experience working at the intersection of education, technology, and public systems, building skills that are highly relevant and future focused. Work in a culture that values ownership, learning, and collaboration, with space to take initiative and grow professionally. Enjoy stability and peace of mind with employee friendly benefits, including health insurance coverage and other supportive policies. If you are driven by purpose, enjoy solving complex problems, and want your work to create visible impact, ConveGenius offers a place to grow while making a difference.
About this listing
- Source: Convegenius's official careers site · still listed there on 7 Nov 2026
- Posted 16 Oct 2026
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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 fast 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
Department · Technology
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Convegenius
ConveGenius leads educational transformation in India with innovative tech solutions aimed at providing quality learning for all. Discover our impact.
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