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Build and scale AI infrastructure for industrial automation, bridging research and production with MLOps and distributed systems.
Build and deploy ML and generative AI models for manufacturing use cases like predictive maintenance and quality control, working with Python, PyTorch, and RAG pipelines in a hybrid Limerick role.
Lead the design and delivery of LLM-powered and agentic AI workflows for JPMorganChase’s internal employee platforms, integrating AI safely into enterprise systems while ensuring reliability and compliance.
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.
Junior business analyst bridges business needs and IT for a premium fashion e-commerce site and app, gathering requirements, documenting processes, and analyzing user data to improve features and conversion.
Build and scale real-time AI systems for crypto market intelligence, using LLMs, RAG, and streaming pipelines to turn social signals into actionable trading insights.
Build and deploy LLM-based AI systems for government services using RAG, fine-tuning, and prompt engineering with Python, LangChain, and cloud ML services.
Builds and maintains data pipelines, deploys ML models, and improves forecasting for a renewable-energy company.
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 ML models to forecast commodity flows and detect anomalies using geospatial and maritime data, working end-to-end from prototyping to production on AWS.
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.
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.
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 maintain large-scale data pipelines and deep learning models to drive AI-driven insights for semiconductor and IoT solutions, using Python, TensorFlow/PyTorch, and cloud platforms.
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 deploy AI/ML pipelines for mobility systems, designing scalable data solutions and analytics dashboards to optimize transport networks and customer experience.
Design and build generative and agentic AI solutions for enterprise clients, including LLMs, RAG, and AI agents, while advising on data strategy and analytics.
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