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Build and deploy optimisation, forecasting, and scheduling models using Python, SQL, Databricks, and MLflow to improve operational decisions for a client’s AI transformation.
Designs, builds, and deploys AI/ML models for industrial use cases like predictive maintenance and computer vision, using Python frameworks and cloud platforms.
Build production ML systems to predict cybersecurity threats and prioritize risks using predictive models, large datasets, and MLOps pipelines.
Build and deploy production-grade AI/ML services for Mastercard’s payments systems, collaborating with data scientists and engineers to ship reliable, scalable features.
Build and deploy large-scale AI solutions for Microsoft’s enterprise customers, using Python/C++ and cloud platforms to analyze data and deliver Responsible AI outcomes.
Build and deploy large-scale AI/ML systems on Google Cloud, designing models and infrastructure for speech, reinforcement learning, or other ML domains to power Google’s products.
Build and maintain scalable data pipelines and ML models to power Kogan.com’s eCommerce operations, enabling data-driven decisions across marketing, logistics, and finance.
Builds and optimizes data pipelines and real-time systems for a major bank using Java, Spark, Python, and Hadoop ecosystem tools to support AI-driven analytics and risk scoring.
Build and deploy AI/ML models for predictive maintenance using time-series sensor data to reduce equipment downtime in industrial and smart-infrastructure settings.
Design, build, and deploy AI/ML models and data-driven solutions to automate tasks, enhance analytics, and support policy decisions for Singapore’s Ministry of National Development.
Build and optimize scalable data pipelines and real-time systems for a major bank using Java, Spark, Python, and the Hadoop ecosystem to support AI-driven analytics and risk scoring.
Build and deploy AI/ML models (forecasting, CV, NLP) in cloud/air-gapped environments, collaborating with engineers to drive operational efficiency and present insights to stakeholders.
Build and automate AI model deployment pipelines for a Singapore bank, enabling secure, scalable delivery of LLM solutions across cloud and container platforms.
Lead the design and deployment of GenAI solutions for insurance, including RAG pipelines, vector databases, and LLM fine-tuning on AWS to deliver context-aware AI capabilities.
Design and build generative and agentic AI solutions for enterprise clients, including LLMs, RAG, and AI agents, while advising on data strategy and analytics.
Build and deploy AI agents and GenAI solutions using Azure AI Foundry, OpenAI, and LangChain, focusing on RAG pipelines, copilots, and agentic workflows.
Build and lead AI-powered digital twin systems using NVIDIA Omniverse, integrating computer vision, LLMs, and real-time 3D simulation for industrial applications.
Design and deploy ML, GenAI, and predictive models using Python, LLMs, RAG, and cloud AI platforms to drive business growth and customer experiences.
Designs and builds AI/ML models and agentic systems to automate workflows, enhance client engagement, and drive decision-making across retail, marketing, and operations using Python, LLMs, and cloud platforms.
Design and deploy GenAI and ML models to transform Chanel’s CRM, retail, and operations data into business value, focusing on responsible AI and end-to-end pipelines.
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