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Build and optimize distributed orchestration frameworks for large-scale ML training and inference in Kubernetes, focusing on resource efficiency and next-gen recommendation systems.
Design and implement Neo4j graph models for banking data, apply graph algorithms to detect fraud, and build real-time investigation dashboards for AML teams.
Build and optimize the backend inference and orchestration layer for an AI assistant that integrates LLMs and multimodal systems into daily workflows.
Builds and maintains scalable backend services in Go/Python and integrates ML models into production for AI/LLM-powered products, while also developing React-based UIs.
Build full-stack web apps and integrate AI features using modern stacks (React, Node.js/Python/.NET, SQL/NoSQL) while leveraging AI coding assistants daily.
Build full-stack web apps and integrate AI features using modern stacks, AI coding assistants, and LLM APIs to deliver enterprise solutions.
Build and maintain SGInnovate’s Deep Tech Central platform using full-stack skills (Next.js, NestJS, PHP, Drupal) and integrate AI features with AWS Lambda, vector databases, and LLM APIs.
Build and deploy full-stack AI applications using Anthropic's Claude ecosystem, including agentic systems, RAG pipelines, and MCP integrations, while working embedded with clients to take AI products from idea to production.
Build and deploy scalable AI systems using Python, LLMs, and GenAI to transform documents into knowledge graphs and automate workflows for industrial and automotive clients.
Design and build scalable Python back-end services in cloud environments, lead AI/GenAI initiatives using libraries like TensorFlow and LangChain, and mentor teams on clean code and best practices.
Build and deploy scalable AI systems using LLMs and GenAI, transforming documents into knowledge graphs and automating code analysis with Python and FastAPI.
Build next-gen AI systems using LangGraph and GraphRAG to enable natural-language queries and insights from distributed data, with Python and AWS.
Lead a team building AI-powered SaaS features for commercial real-estate tools, designing LLM agents, RAG pipelines, and MCP integrations in a Node.js/Python stack.
Builds and maintains AI-enabled apps, agents, and workflow automations for healthcare workflows, integrating LLMs, RAG systems, and enterprise tools to improve efficiency and knowledge reuse.
Build production-grade AI agents and retrieval systems using Microsoft Foundry, Azure AI Search, and MCP for enterprise clients in the Middle East and Africa.
Build ML models that enrich and categorize millions of transactions, detect anomalies, and assess risk for Saudi Arabia’s first retail Open Banking platform.
Design, train, and deploy AI/ML models and generative AI solutions using cloud-native platforms like GCP Vertex AI, Azure ML, or AWS SageMaker.
Build and maintain the data pipelines and retrieval layer that power Mirai’s Generative AI products on AWS, including vector stores, embeddings, and governed datasets.
Builds and deploys Python backend services for AI/ML apps, integrating models, APIs, and databases to move prototypes into production.
Build ML forecasting models and LLM pipelines to analyze tax-compliance support data, then translate insights into clear narratives for leadership.
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