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Build and deploy ML/AI models (including GenAI) for pricing, personalization, and fraud detection in a restaurant-tech SaaS platform.
Build and scale ML pipelines to normalize telematics data, detect anomalies, and forecast metrics for logistics and insurance workflows using time-series and geospatial models.
Lead a team building generative AI and deep learning models (NLP, computer vision) to solve business problems across claims, marketing, and other departments.
Build and maintain scalable data pipelines that securely connect enterprise data with GenAI platforms like Azure OpenAI and AWS SageMaker, ensuring compliance and high-quality AI workloads.
Designs, builds, and deploys AI-powered applications to automate business processes and solve real challenges within a financial services company.
Build and deploy ML models end-to-end for e-commerce pricing, forecasting, recommendations, and A/B testing to drive revenue and margin.
Design and maintain cloud infrastructure and CI/CD pipelines for AI/ML systems, automating deployments and monitoring production AI workloads.
Lead a team to build, optimize, and deploy AI models on AWS using SageMaker, Bedrock, and Rekognition, while architecting scalable data pipelines with Athena, Redshift, and OpenSearch.
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.
Lead the design, optimization, and deployment of AI/ML models on AWS, using SageMaker, Bedrock, and vector databases to build scalable, cloud-native solutions.
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.
Build and secure a scalable AI/ML platform on AWS SageMaker, EKS, and Azure DevOps to enable rapid healthcare model deployment and experimentation tracking.
Build and maintain ML models and data pipelines in Python and PySpark on AWS SageMaker, focusing on recommendation and churn prediction systems for real business impact.
Build and maintain ETL pipelines in Python and SQL to move and transform data, working with AWS services like S3 and Athena.
Build and maintain ML models and data pipelines using Python, PySpark, and AWS SageMaker for advanced analytics projects.
Design and deploy ML models, build LLM-based solutions, and create robust data pipelines on AWS SageMaker for an insurance company.
Design and automate scalable SageMaker environments for ML model deployments across Europe using AWS, Python, and CI/CD pipelines.
Senior DevOps Engineer designs and automates AWS cloud infrastructure with AI/ML services like Bedrock and SageMaker, deploying secure, scalable CI/CD pipelines and containerized inference on EKS/ECS.
Lead a team to design and deliver AI/ML solutions for Workday products, including predictive analytics and generative AI, while mentoring staff and managing line responsibilities.
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