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Senior Azure Data Engineer designing, implementing, and optimizing scalable data solutions on Azure and Microsoft Fabric for an aeronautical software company, working with ADF, Databricks, Synapse, ADX/KQL, Spark, and Power BI.
The Data Engineer will build and maintain scalable data pipelines to integrate Machine Learning model predictions into production data products. The role involves using Python, SQL, Spark, and Databricks within a hybrid work environment in Barcelona.
Build and operate Python backend services powering ML and generative AI solutions (LLMs, RAG, vector DBs) on AWS, collaborating across product, security, and platform teams in Singapore.
Lead Data Engineer (MLOps) at Allianz UK Personal enhancing MLOps capability, defining technical direction, and leading delivery of cloud-based Data Science products using Azure, Python, SQL, dbt, Kubernetes, Docker, Terraform, Databricks, and Azure DevOps/GitHub.
Data Engineer building scalable data pipelines and MLOps infrastructure for ML models at a pharmaceutical company, collaborating with Data Scientists to take AI concepts from development to production.
The Data Engineer will design and maintain production-grade data pipelines and reporting using GCP and BigQuery. They will collaborate with cross-functional teams to manage data models, ensure data quality, and scale MLOps capabilities.
Data Engineer designing, building, and maintaining production data pipelines and reporting on GCP/BigQuery with dbt, Python, and SQL for Ki, an algorithmic insurance carrier.
This role involves building and scaling GenAI-powered platforms to improve developer productivity within a global financial institution. The engineer will work across the full stack using Python, TypeScript, React, or Go, while applying cloud-native and DevSecOps principles.
Full-stack engineer building GenAI platforms at Citi London, using Python, TypeScript/React/Go, Kubernetes, and cloud-native tech to boost developer productivity.
The DevOps Engineer will design, build, and scale infrastructure for AI-driven products, focusing on reliability, security, and MLOps workflows. The role involves working with AWS, Terraform, and Kubernetes to support engineering and data science teams.
DevOps Engineer at a London-based psychological science startup, owning cloud infrastructure, CI/CD pipelines, and observability while supporting AI/ML workloads on AWS.
Founding ML Engineer building production-grade ML pipelines and deploying LLMs/generative models from the ground up at an early-stage AI company, using Python, PyTorch/TensorFlow/JAX, and cloud infrastructure.
abra professional services is seeking a Senior Generative AI Engineer! This is a hands-on role combining deep technical expertise with strategic thinking to design, develop, and implement advanced Generative AI…
Senior Data Engineer owning ETL/ELT pipelines, data warehouse design, and streaming data systems for Carousell Group's recommerce marketplace (Mudah.my), using SQL, Python, Apache Airflow, and cloud data warehouse technologies.
The AI DevOps Engineer will design and maintain infrastructure, CI/CD pipelines, and MLOps environments to support the deployment of AI solutions. The role requires leveraging generative AI tools for automation and scripting while collaborating with data scientists and developers to ensure scalable, secure production operations.
DevOps Engineer at an online motor insurance company in Madrid, focused on building and operating reliable, scalable systems using AWS, Kubernetes, Python, and Infrastructure as Code (Pulumi).
The MLOps Engineer will manage machine learning workflows and infrastructure using tools like Azure ML, AWS SageMaker, MLflow, Docker, and Kubernetes. This is a remote role at a software development company with a 20-year history.
Machine Learning Engineer at NTT DATA in Peru, building and maintaining ML solutions using Python, GitHub Actions, and orchestration tools like Airflow within a large IT services consultancy.
The MLOps Engineer will build and maintain the data infrastructure and automation for an AI team, focusing on offline-capable environments and data pipeline management. The role involves managing Linux servers, containerization, and ML lifecycle tools like MLflow or DVC to support data workflows.
As a Senior Data Engineer Consultant, you will design and industrialize data platforms, build ETL/ELT pipelines, and manage large-scale data architectures using cloud technologies like AWS, GCP, or Azure. You will collaborate with data scientists and engineers to ensure data scalability and security while mentoring team members.
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