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Build and deploy ML models for predictive maintenance and energy optimization using Python, FastAPI, and Azure ML in ETAP’s electrical digital twin platform.
Designs, builds, and maintains AI-driven data pipelines and ML applications in Python to power business decisions and strategy.
Lead the architecture and strategy of JLL’s enterprise data platform, consolidating global systems into a unified, scalable data layer to power AI-driven insights and analytics for commercial real estate.
Build, deploy, and maintain ML models and data pipelines in Python/SQL, using scikit-learn, PyTorch/TensorFlow, and MLOps tools like MLflow to productionize insurance-focused solutions.
Build, deploy, and maintain ML models and data pipelines in Python/SQL, using scikit-learn, PyTorch/TensorFlow, and MLOps tools like MLflow to move prototypes into production.
Build and optimize AI/ML pipelines and real-time data systems for blockchain intelligence, enabling faster threat detection and insights for crypto businesses and governments.
Build and maintain scalable data pipelines on Databricks and Azure, optimizing ETL/ELT processes to support analytics and ML initiatives for an insurance-focused team.
Build and maintain scalable data pipelines and infrastructure to power AI applications using LLMs, retrieval systems, and agentic architectures for enterprise clients.
Build and maintain scalable data pipelines on Databricks and Azure to feed analytics, ML, and reporting for an insurance company.
Build and maintain scalable data pipelines and infrastructure to power AI/ML features in Tebra’s healthcare EHR platform, ensuring reliable, high-quality datasets for model training and production inference.
Senior engineer builds and deploys LLM-powered agents and RAG systems for clients, owning presales scoping through production deployment with Python and cloud tooling.
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 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 production-grade AI tools and data pipelines for the Group CEO, turning executive problems into reliable LLM-enabled workflows and decision-support systems while aligning with maritime and trading operations.
Designs and deploys cloud-native, Kubernetes-based AI infrastructure and hybrid architectures for enterprise customers, focusing on GPU clusters and MLOps workflows.
Lead a team to build and maintain Swire Properties’ enterprise data platform, integrating CRM and leasing data to power analytics, AI, and GenAI use cases while ensuring security, compliance, and data quality.
Build and optimize speech AI models (ASR, diarization) and pipelines, deploy ML services, and improve accuracy/latency for production systems.
Build and deploy scalable speech AI systems, training and optimizing ASR, diarization, and analytics models using PyTorch and modern ML toolkits.
Build autonomous agents, data pipelines, and executive AI tools for a CEO while ensuring scalable, secure MLOps/LLMOps systems.
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