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Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
Build and maintain data pipelines and warehouses for AI projects, using PySpark, Databricks, and Azure services to centralize and process large datasets.
Build and deploy ML models and agentic systems to improve clinical trial success rates using Python, FastAPI, TensorFlow/PyTorch, and AWS.
Build and deploy production-grade AI systems end-to-end, from data pipelines and ML models to scalable deployment and monitoring using Python, PyTorch, and MLOps tools.
Build and deploy AI-driven data analytics and generative AI solutions on Azure and GCP, including MLOps pipelines and agentic AI workflows.
Act as a technical advisor during pre-sales, designing AI/LLM and modern data platform solutions for enterprises, and guiding clients from discovery to implementation.
Build and deploy ML models and AI solutions for global clients, from LLMs to optimization engines, using Python, cloud platforms, and MLOps practices.
Lead the design and deployment of AI/ML systems for global clients, including optimization engines and LLM-powered recommendation systems using Python, AWS, and MLOps practices.
Build and deploy ML models and AI systems for enterprise clients, focusing on LLMs, NLP, and computer vision to solve industrial, automotive, and software-engineering challenges.
Build and deploy AI/ML models for industrial use cases like predictive maintenance and process optimization, using Python, TensorFlow/PyTorch, and MLOps pipelines.
Build and deploy data-driven solutions using Python, ML, and Azure to optimize building systems and sustainability for Johnson Controls' smart-city and decarbonization products.
Build and evaluate data-driven solutions for smart buildings and climate tech using Python, Azure ML, and SQL; track impact with attribution methods.
Build AI-powered location intelligence models and APIs that turn TomTom’s map and traffic data into actionable insights for enterprises, governments, and partners.
Build and maintain AWS-based data pipelines and ML workflows, turning datasets into insights and scalable analytics for clients across industries.
Build and maintain data pipelines and infrastructure for AI solutions, working with Spark, Python, and LLMs to support machine learning models and predictive analytics.
Senior Data Engineer builds scalable data pipelines and ML analytics for chemical manufacturing, focusing on predictive maintenance, optimization, and real-time streaming using Python, SQL, and Kubernetes.
Builds and maintains ETL pipelines, deploys ML models to production, and monitors data flows and model performance using Python, SQL, and Azure.
Build and maintain ETL pipelines, deploy ML models, and monitor data flows in a fintech environment using Python, SQL, and Azure.
Build and automate predictive models, ETL pipelines, and monitoring systems using Python, Databricks, and Azure to power AI-driven marketing analytics and campaign optimization.
Design and build scalable data pipelines and ML-ready datasets for chemical manufacturing, enabling predictive maintenance, optimization, and automation using Python, SQL, and cloud-native tools.
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