#SGunited Jobs Data & AI Platform Engineer

Design and implement OCR, VLM, and multimodal AI pipelines leveraging state-of-the-art models (e.g., GPT- [4/5]o, vision-language models, Text-to-Speech) for accurate content extraction, layout understanding, and table/chart interpretationDesign, build, productionize, and support scalable document parsing and content extraction pipelines on a modern hybrid cloud platform, handling structured and unstructured data including PDFs, PPTX, Excel, Word, images, scanned documents, videos, audios, charts, tables etcDevelop and optimize embedding models, including fine-tuning and domain adaptation to support organization-specific terminology, keywords, and semantic search use casesImplement knowledge ingestion, indexing, and retrieval pipelines for RAG (Retrieval-Augmented Generation) and agentic GenAI systems, ensuring high recall, precision, and low-latency retrievalMake an Impact by:Build and maintain data ingestion pipelines for batch and streaming data sources using tools/library like Kafka, LlamaIndex, LangChain, PyMuPDF, MSAL etc.Implement layout-aware parsing to accurately preserve document structure, hierarchy, and reading order (using OCR, VLM, and multimodal AI solutions).Extract accurate numeric and semantic data from complex charts and irregular tables while preventing hallucinations.Assist in integrating data from diverse source systems (files, APIs, databases, streaming)Implement, fine-tune, and optimize embedding models to support organization-specific terminology, improving semantic search, retrieval accuracy, and downstream GenAI performance.Help maintain metadata and pipeline documentation for transparency and traceabilityParticipate in integrating pipelines with tools such as Microsoft Fabric, Databricks, Delta Lake, and other platform componentsBuild and maintain knowledge base and RAG solution on cloud (Azure)Implement and operate knowledge base storage, lifecycle management and embedding/vectorizationContribute to automation efforts using version control and CI/CD workflowsApply basic data governance and access control policies during implementation.Skills for Success: Bachelor’s degree in Computer Science, Engineering, or a related field1–3 years of experience in data engineering or data platform development. Fresh graduates encouraged to apply as well.Proven ability to independently build basic batch or streaming document processing pipelinesHands-on experience with Python, PyTorch, PEFT, LoRA, OCR, VLM, LLM, prompting, Text-to-Speech models and SQL for data transformation and validationFamiliarity with Apache Spark (especially PySpark) and large-scale data processing conceptsExperience with implementing knowledge base and RAG solutions for agentic AI use casesSelf-starter with strong problem-solving skills and a keen attention to detailAble to work independently while collaborating effectively with senior engineers and other stakeholdersStrong documentation and communication skills