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Build and maintain the AI platform and data lakehouse, automating operations and integrating services with APIs and cloud infrastructure using Python, Kubernetes, and MLOps tools.
Build and improve AI-powered financial research tools using LLM, RAG, vector search, and agentic workflows for a market intelligence platform.
Build and deploy enterprise-grade GenAI and ML applications for asset management workflows, integrating LLMs, RAG, and vector databases with full-stack Python/React systems in a regulated environment.
Build and optimize production-grade LLM systems, integrating commercial APIs and self-hosted models, and implementing RAG pipelines and end-to-end LLM workflows.
Build and own a large-scale Web3 big data platform that ingests on-chain transactions, trading behavior, and user profiles, then layer AI/ML tools for fraud detection, risk modeling, and natural-language data querying.
Build and deploy enterprise-grade LLM applications using RAG, AI Agents, and vector databases like Milvus/Qdrant. Develop Python-based AI workflows and APIs for real-world production use.
Build and deploy production-grade LLM chatbots and RAG pipelines using commercial APIs and self-hosted open-source models, optimizing for latency, cost, and reliability.
Builds and maintains full-stack web apps while integrating AI/Generative AI models to enhance user experiences and functionality.
Lead training, alignment, and optimization of large language models using RLHF, SFT, and quantization; build reward models, red-team models, and optimize inference pipelines in Python/C++/Rust.
Design and operate PostgreSQL clusters and vector search systems to power Kraken’s crypto exchange and AI features, focusing on performance, reliability, and automation.
Builds enterprise GenAI apps with Python, LangGraph, and RAG pipelines, integrating LLMs and vector search for AI agents and chatbots.
Protect Absa’s AI systems by designing secure AI architectures, detecting AI-specific threats, and running offensive security tests like prompt injection and agent manipulation.
Design and lead enterprise AI solutions for Australian clients, building secure LLM/RAG architectures and rapid PoCs while mentoring AI engineers.
Builds and scales cloud-native backend services in Python/Node.js, using microservices, Docker, Kubernetes, and Azure, with a focus on security and performance.
Build and optimize GenAI systems using LLMs, prompt engineering, RAG, and agent workflows with frameworks like LangChain. Integrate APIs, vector databases, and external tools for scalable AI solutions.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to improve search, recommendations, and automation.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to automate workflows and improve user experience.
Build and scale the backend platform that powers AI-driven travel experiences, integrating ML models and vector search for real-time personalization at global scale.
Build and deploy backend services for AI/ML models, integrating LLMs, vector databases, and RAG pipelines using Python, FastAPI, and cloud platforms.
Build and maintain LLM servers (Llama, Mistral, GPT API) and deploy AI agents that automate tasks like reminders, reports, and paperwork using vector databases and RAG pipelines.
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