AI/ML ENG IMM Joinner

Role & responsibilities We are looking for an experienced AI/ML Engineer to own and advance our core AI pipeline. The ideal candidate will have strong hands-on experience in Generative AI, NLP, and production ML systems. You will be responsible for maintaining, improving, and scaling the AI infrastructure that powers our child developmental assessment platform. Key Responsibilities Design and build end-to-end AI pipelines for multimodal data processing including video, audio, image, and text Need to have worked on recommendation models, neural networks and LLMs. Integrate and work with Large Language Models and Vision Language Models for intelligent data extraction and reasoning Build and maintain RAG pipelines for grounded, context-aware AI outputs Develop and orchestrate agentic AI workflows for complex multi-step automation Build recommendation systems and personalization engines based on user behaviour and segmentation Deploy and maintain AI models in production cloud environments with proper monitoring and evaluation Expose AI capabilities as scalable REST APIs for product integration Perform exploratory data analysis and derive insights to support product decisions Collaborate with cross-functional teams to translate requirements into AI solutions Build evaluation and testing frameworks to ensure model quality, reliability, and safety Stay current with the latest advancements in LLMs, multimodal AI, and agentic systems Required Skills and Experience Generative AI and LLMs Hands-on experience building RAG pipelines including document processing, chunking strategies, embedding models, and vector databases Experience working with Vision Language Models for multimodal input understanding Strong prompt engineering skills system design, few-shot learning, chain-of-thought, structured output Experience with LangChain and LangGraph or similar orchestration frameworks for agentic workflows Familiarity with LLM API integration and multi-model pipeline design Understanding of hallucination mitigation and output grounding strategies in production systems Machine Learning and Deep Learning Strong foundation in NLP text classification, sequence modeling, and transformer-based architectures Experience fine-tuning or working with pretrained language models Hands-on experience with graph-based learning or relational modeling approaches Experience with multi-label and multi-class classification problems Proficiency in PyTorch and/or TensorFlow and Keras Experience with MongoDB for data storage, retrieval, and integration with AI pipelines MLOps and Deployment Docker containerization of ML models and services GCP Cloud Run or equivalent serverless deployment platforms CI/CD pipeline setup and management using GitHub Actions or similar tools FastAPI or similar frameworks for building and exposing ML model APIs Model versioning, monitoring, and production maintenance What We're Looking For 6+ years of hands-on experience in AI/ML engineering Strong problem-solving mindset with ability to work on ambiguous, open-ended problems Experience taking AI systems from research or prototype to production Self-driven, ownership mindset Strong communication skills .