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Builds predictive and prescriptive analytics models for utility/energy systems using Python/Java and deploys them via MLOps pipelines.
Postdoctoral role researching machine learning, federated learning, and explainable AI for healthcare, energy, and smart infrastructure, deploying models on edge/cloud and publishing findings.
Leads AI/ML projects, designs models, and mentors engineers to build and deploy AI solutions for business innovation.
Senior AI/ML Engineer builds, validates, and deploys machine learning and deep learning models using Python, TensorFlow, and PyTorch to power AI-driven products and business solutions.
Designs, builds, and validates AI/ML models and deep learning algorithms to power data-driven solutions for a media-focused company.
About the Role You’ll work alongside experienced engineers to improve our AI-enabled plan ingestion pipeline—from raw PDFs to clean, dependable outputs that power takeoff, design, and downstream automation. You’ll…
Build and maintain a secure, scalable data/ML platform on AWS SageMaker, EKS, and Azure DevOps to enable AI model experimentation and deployment for healthcare.
Design and deploy AI/ML systems and data pipelines to transform raw data into scalable, business-impacting insights for clients.
Builds and maintains ETL pipelines and data warehouses on GCP to power AI-driven marketing, using Python, dbt, Airbyte, and Airflow.
Build and maintain scalable data pipelines and production-grade ML systems for clinical trials, pharmacovigilance, and drug manufacturing at a global pharma company.
Build and operate AWS’s European Sovereign Cloud, automating and scaling EC2, S3, Lambda, and Bedrock for EU customers while leading on-call rotations and operational excellence.
Build and operate AWS’s European Sovereign Cloud, automating and scaling EC2, S3, Lambda and other services to ensure high availability for EU customers.
Design and build scalable AI/data-science architectures (LLMs, RAG, ML) in cloud and on-prem, then advise customers and implement solutions in Python, Azure ML, and Kubernetes.
Design and maintain AWS-based data pipelines, cloud data platforms, and AI/ML solutions using Python, Spark, and AWS services like S3, Glue, Redshift, and SageMaker.
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 maintain ML pipelines using Airflow, MLflow, and GCP; migrate on-premise systems to cloud-native environments and ensure scalable, reliable data workflows.
Builds and maintains ETL pipelines, deploys ML models to production, and monitors data flows and model performance using Python, SQL, and Azure.
Design and optimize scalable data pipelines using Databricks, Apache Airflow, and Spark to process streaming and batch data for enterprise clients across industries like aerospace, energy, and automotive.
Build and optimize scalable data pipelines using Databricks, Spark, and Azure to power AI/ML solutions for global enterprises across aerospace, energy, and automotive sectors.
Administers SAS environments (SAS 9 and SAS Viya), configures components, and supports model deployment for ING’s analytics teams.
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