Sr. ML Engineer- Generative AI

• 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.

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

• 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.