About this role
The AI/ML Engineer designs, develops, and deploys advanced machine learning, LLM, RAG, and speech-to-text (Whisper) solutions that enable national-scale AI capabilities. The role supports the Chief AI Officer and Chief Data Officer in delivering AI-driven insights, prototypes, and production-grade models to enhance national digital platforms and services. Key Responsibilities Design and implement RAG pipelines and vector databases to enable AI-driven search, knowledge retrieval, and decision-support systems for PDA platforms. Train, fine-tune, and evaluate LLMs, including domain-specific models, to support national-scale services and automated decision-making. Develop and deploy Whisper-based speech-to-text models for transcription, analytics, and accessibility features in PDA applications. Build scalable ML pipelines, APIs, and inference services integrated into PDA’s digital ecosystem. Conduct model evaluation, optimization, and monitoring, ensuring performance, scalability, and reliability for critical national platforms. Collaborate with product, data, and engineering teams to integrate AI/ML features into national platforms such as the National Job Portal, DPI, and digital public services. Ensure Responsible AI principles, including fairness, transparency, privacy, and ethical model deployment, in all AI initiatives. Stay updated on emerging AI technologies and advise PDA leadership on strategic adoption for national digital services. Qualifications Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science. Atleast 5 years hands-on experience with LLMs, RAG systems, Whisper, vector databases, and GPU-based ML pipelines. Core Skills & Competencies Python, PyTorch, TensorFlow LangChain, LlamaIndex, or equivalent LLM frameworks ML pipeline development & MLOps Vector databases & embeddings-based retrieval Speech processing & Whisper-based transcription Containerization & orchestration (Docker, Kubernetes) Model evaluation, monitoring, and optimization Responsible AI, fairness, and ethical deployment