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Build and maintain full-stack data infrastructure for Singapore’s education sector, integrating cloud services, ETL pipelines, and analytics tools to support AI-driven digital transformation.
Leads cloud-native big data pipelines and GenAI model infrastructure at a global insurer, collaborating with AI/ML and analytics teams to build scalable solutions for risk management and business insights using Spark, Kubernetes, and AWS SageMaker.
Designs and implements cloud/hybrid data pipelines, advanced analytics, and AI-driven solutions (e.g., ML models, dashboards) to transform raw data into actionable insights for enterprise clients. Core tech: Azure/AWS/GCP, Python/SQL, Spark, Kafka, and Azure OpenAI.
Build and scale ML Ops pipelines in Scala/Python, automate model deployment with Spark/Ray, and optimize cloud costs on AWS/GCP/Azure.
Builds and deploys enterprise-grade GenAI full-stack solutions using React/Angular frontends, Python/Node.js backends, and cloud DevOps, integrating LLMs and document-processing pipelines for healthcare workflows.
Design and build an enterprise ML platform on AWS SageMaker Unified Studio, migrating from a fragmented toolchain to a governed platform covering the full ML lifecycle.
Build and deploy marketing ML models using Python, PySpark, and AWS services; engineer scalable data pipelines and automate analyses for ad-tech and customer analytics.
Build and run cloud-native data platforms and pipelines using Python, SQL, Spark, and cloud tools to enable AI services for enterprise clients.
Build and maintain computer-vision models that detect building defects from drone and telephoto imagery, using PyTorch, CUDA, and AWS GPU infrastructure.
Build and deploy ML models (propensity, recommendation, LTV) on AWS SageMaker and use LLMs for personalisation and analytics to drive revenue growth in a digital bank.
Own commercial analytics for a global fintech/ecommerce platform, building trusted metrics and dashboards in dbt, Tableau, and Looker to drive revenue, margin, and risk decisions.
Senior consultant builds and maintains AWS-based MLOps pipelines for a quant hedge fund, migrating researchers from an on-premise grid to cloud compute while ensuring fast, interactive workflows.
Build and deploy GenAI and agentic AI systems for pharma clients using Microsoft Copilot Studio, ChatGPT Enterprise, and AWS Bedrock, integrating structured and unstructured data pipelines.
Design and advise customers on generative AI and ML solutions using AWS services like Bedrock, SageMaker, and Nova, including RAG pipelines, agentic workflows, and model customization.
Design and evangelize AWS AI/ML solutions for enterprise customers, building demos and workshops that showcase Agentic AI applications using services like Amazon Bedrock and SageMaker.
Designs and builds secure, reusable AI reference implementations for AWS customers, turning validated security patterns into deployable code and documentation for regional adoption.
Build and deploy production-ready AI and multi-agent systems for healthcare, focusing on secure, compliant generative AI workflows using LLMs, RAG pipelines, and cloud platforms.
Design and deliver enterprise-grade AI systems using LLMs, RAG, agentic workflows, and cloud-native platforms while ensuring security, compliance, and scalability for Nordic customers.
Lead AI strategy and build predictive models to drive enterprise transformation, overseeing data science teams and deploying cutting-edge AI solutions.
Leads a tiger team to modernize AI/ML platforms, integrating LLMs (RAG, embeddings) and automating data pipelines for customer identity resolution, while mentoring teams on next-gen AI development and .NET/React-based infrastructure.
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