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Principal AI Data Engineer builds and prototypes AI, GenAI, and Agentic AI solutions using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI, and MLflow.
Build and lead AI/ML systems for energy infrastructure, including predictive maintenance, anomaly detection, and time-series forecasting on industrial sensor data.
Build and maintain automated test infrastructure for data science microservices, APIs, and databases to ensure reliability and scalability of a logistics platform.
Build and deploy ML/AI models (including GenAI) for pricing, personalization, and fraud detection in a restaurant-tech SaaS platform.
Build and maintain scalable Databricks pipelines (Delta Lake, Spark SQL, MLflow) to integrate and transform data for large-scale analytics and ML projects.
Build and maintain scalable Databricks pipelines using Delta Lake, Spark SQL, and MLflow to industrialize ML models and AI workflows for large-scale analytics.
Build and optimize high-performance data platforms using Databricks, Spark, and multi-cloud tools to deliver scalable data insights and pipelines for enterprise clients.
Lead the build and operation of MLOps platforms on AWS for autonomous-driving ML workloads, using Ray, Kubernetes, Airflow, MLflow, and CI/CD pipelines.
Build and deploy scalable ML and GenAI pipelines using Python, Azure ML, and MLflow to productionize models and APIs for a global ingredients and sustainability-focused company.
Architect and own the MLOps infrastructure for adaptive AI models in a regulated medical-device setting, defining versioning, validation, and PCCP-style change-control processes.
Traduire un besoin métier en cas d’usage IA qui tient la route, c’est le cœur de votre métier — et c’est aussi le nôtre. Chez Smile, le Product Owner IA n’aligne pas des fonctionnalités : il garantit que la solution…
Design and maintain cloud infrastructure and CI/CD pipelines for AI/ML systems, automating deployments and monitoring production AI workloads.
Build and deploy ML models using Python, TensorFlow/PyTorch, and MLOps tools; integrate AI features into products and optimize performance.
Build autonomous AI agents and data pipelines using LangChain/LangGraph or Google Vertex AI Agent Builder to automate analytics and decision-making at scale.
Senior AI Engineer designs and deploys enterprise AI systems using TensorFlow, PyTorch, and LLM APIs, building scalable ML pipelines and computer vision/NLP solutions for fintech and healthcare clients.
Build and deploy multi-step AI agent workflows using LangChain, LlamaIndex, and platforms like Azure AI Studio Agents or AWS Bedrock Agents, integrating APIs and databases for automation.
Build and deploy AI/ML perception systems for autonomous robots and drones, fusing sensor data to enable safe navigation in warehouses and industrial settings.
Engineer open-source data/AI platforms using Python and Kubernetes, deploying ML pipelines with Kubeflow, MLFlow, DVC, and Feast for cloud and on-prem environments.
Lead end-to-end ML/AI model development and MLOps at a construction and infrastructure firm, setting standards for reproducibility, validation, and responsible AI while mentoring junior scientists.
Build and maintain scalable MLOps pipelines to deploy, monitor, and manage machine learning models in production using cloud platforms, CI/CD, and Kubernetes.
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