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Design and architect scalable AI and machine learning platforms on Microsoft Azure, focusing on Agentic AI, ML optimisation, and intelligent edge solutions for enterprise clients.
Build and deploy LLM-based AI systems for government services using RAG, fine-tuning, and prompt engineering with Python, LangChain, and cloud ML services.
Build ML models and data pipelines for fraud detection and payment optimization in a global fintech platform.
Build and deploy scalable data pipelines and ML models for fraud detection, risk management, and customer analytics in the financial sector using Python, Spark, and cloud platforms.
Builds and maintains data pipelines, deploys ML models, and improves forecasting for a renewable-energy company.
Build and own Shiftbase’s BigQuery + Dataform warehouse from scratch, designing layered architectures and ELT pipelines that feed clean, governed HR data to teams and AI initiatives.
Build and lead Vandebron’s open data lakehouse, shaping architecture, governance, and MLOps to power green-energy analytics and AI-driven customer intelligence.
Build and maintain data platforms, pipelines, and ML infrastructure for an asset-management firm, using cloud tools like GCP/AWS and BI platforms such as Power BI or Tableau.
Build and integrate computer-vision models into client stacks using PyTorch, OpenCV, and Gradio; prototype cutting-edge algorithms and ship them in Datature’s MLOps platform.
Lead the design and delivery of end-to-end scalable machine learning systems using Python, TensorFlow, and cloud platforms, while mentoring teams and shaping ML strategy for high-stakes client projects.
Build and deploy scalable AI systems that turn physical-world data into enterprise intelligence, optimizing energy and operations for industries like climate tech.
Design and build production-grade AI/ML platforms and MLOps pipelines for clients, using Python, cloud (GCP/AWS/Azure), Terraform, and tools like Vertex AI and Kubernetes.
Build and maintain scalable data pipelines and AI systems using Python, SQL, NLP, and LLM technologies to support data-driven decision-making and GenAI solutions.
Lead the development of foundation models for Grab’s marketplace, designing transformer architectures and scalable training pipelines using PyTorch and DeepSpeed.
Design and deploy AI-powered solutions using Microsoft Azure AI services, building scalable models and integrating them into enterprise applications.
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 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, train, and deploy AI/ML models (e.g., time-series, CV, NLP) to solve business problems, then monitor and iterate them in production with MLOps tooling.
Build and automate AI model deployment pipelines for a Singapore bank, enabling secure, scalable delivery of LLM solutions across cloud and container platforms.
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