Walk-in || Direct Walk In - AIML Engineer -09 Sep 26 @Bangalore

• Five or more years of software engineering experience, including two or more years building production AI/ML or LLM-based systems • Strong, hands-on understanding of embeddings and embedding models, including how to choose, evaluate, and apply text and multimodal embeddings for semantic search and recommendation • Experience with vector databases and modern retrieval patterns, including retrieval-augmented generation • Experience building recommendation, matching, or ranking systems that combine semantic similarity with structured-attribute or rule-based filtering • Working knowledge of computer vision or document-understanding techniques for extracting information from images, diagrams, or scanned technical documents • Practical experience turning messy structured and semi-structured data (such as product catalogues or PIM exports) into clean, model-ready datasets • Demonstrated experience building agentic systems: tool use, multi-step planning, evaluation, and guardrails • Hands-on experience with AWS AI/ML services (Amazon Bedrock, SageMaker, OpenSearch or other vector stores, Lambda, ECS/EKS for inference) • Strong Python skills and a track record of shipping ML/LLM features to production with proper testing and monitoring • Working knowledge of feature stores, model registries, and MLOps tooling • Comfortable collaborating across architecture, data, backend, and front-end team Role & responsibilities

Preferred candidate profile

• Experience with multimodal models that jointly reason over text and images, or with fine-tuning vision and embedding models for a specialised domain • Familiarity with product-catalogue, configurator, fitment, quoting, or guided-selling use cases • Experience operationalising LLMs in regulated, B2B, or enterprise environments • Familiarity with manufacturing or industrial product data, including engineering drawings and dimensioned specifications • AWS Certified Machine Learning Specialty or AI Practitioner certification • Contributions to open-source AI/ML projects or applied research