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Data Scientist / Machine Learning Engineer
Build, train, and deploy ML/DL models (NLP, clustering, anomaly detection) in Azure/Google Cloud, integrating them into production pipelines using MLOps and cloud-native tools.
Data Scientist / MLOps Engineer - 100% teletrabajo - Remoto
Build and deploy ML models and MLOps pipelines using Python, Spark, SQL, and FastAPI in a fully remote role.
Senior Data & AI Engineer / MLOps Engineer – Productivización de Soluciones de IA - valència
Senior Data & AI Engineer / MLOps Engineer to industrialize AI solutions, deploying ML models and LLM agents into production while ensuring data pipelines, security, and governance meet enterprise standards.
Data Scientist / MLOps Engineer - 100% teletrabajo
Build and deploy ML models and data pipelines using Python, Spark, and FastAPI, iterating from experimentation to production in a fully remote role.
Senior Data & AI Engineer / MLOps Engineer – Productivización de Soluciones de IA
Senior Data & AI Engineer / MLOps Engineer to industrialize AI solutions, deploying ML models and LLM agents into production while ensuring data pipelines, security, and governance meet financial-sector standards.
Data Engineer
Build and maintain scalable ETL pipelines, cloud data infrastructure, and MLOps workflows in AWS using Spark/Databricks, while integrating agentic AI and LLM-based solutions for Zurich Insurance Group’s Technology Delivery Center.
Data Engineer with Azure DevOps
Build and automate data pipelines in Azure Data Factory and MLOps tooling in Azure DevOps to move and transform data for analytics and AI workloads.
DevOps Engineer
Senior DevOps Engineer designs, migrates, and operates AWS cloud platforms for enterprise clients, building scalable CI/CD pipelines and containerized workloads with Terraform and Docker.
Senior AI Platform Engineer
Design and run Absa’s multi-cloud AI platform (AWS Bedrock, Databricks, Azure AI Foundry) that powers 43 live AI projects across ten countries, focusing on FinOps, zero-trust security, agentic AI infrastructure, and enterprise-grade observability.
AI Platform Engineer (Cloud)
Build and run a secure, multi-cloud AI platform for a bank, deploying services on AWS Bedrock, Databricks, Azure AI, Hugging Face and Kubernetes while optimizing costs, security and observability for enterprise-scale AI workloads.
Machine Learning Data Engineer
Build and deploy AI-driven data pipelines on AWS Bedrock to automate document processing and compliance workflows for corporate secretarial and accounting use cases.
AI Data Engineer
Design and deploy AI-driven data pipelines on AWS, fine-tuning ML models for document processing and corporate compliance in a fast-paced energy-adjacent environment.
Data Engineer - QuantumBlack
Builds and maintains scalable data pipelines, GenAI applications, and advanced analytics platforms for McKinsey’s QuantumBlack AI division, collaborating with clients and cross-functional teams to solve high-impact business problems using Python, PySpark, Kubernetes, and cloud technologies.
(Senior) DevOps Engineer- AI Innovation
Design and maintain scalable cloud infrastructure and CI/CD pipelines for AI/ML platforms, using Terraform, Kubernetes, and AWS/GCP.
Backend Engineer AI Solutions
Build and maintain secure backend services for AI, ML, and generative AI solutions, including model pipelines, APIs, and RAG systems, while ensuring responsible AI practices and compliance.
Backend Engineer, Marketplace Intelligence & Data - MPIE
Builds and maintains backend services for Shopee’s marketplace intelligence platform, integrating ML tools for recommendations, user profiling, and data products.
Data Engineer: Real-Time Analytics & Automation
Builds and maintains real-time data pipelines and analytics databases to power instant business decisions using SQL, Python, and dimensional modeling.
Data Engineer - Mid
Builds and maintains data pipelines and databases to power real-time insurance pricing models using SQL, Python, and dimensional modeling.
GCP Data & MLOps Engineer — Remote Cloud Security
Designs and operates GCP-based data pipelines, AI/ML models, and cloud-native platforms using Dataflow, Kubeflow, BigQuery, and Django, while applying DevOps/MLOps best practices in a defence-focused environment.
GCP Data Engineer & MLOps Specialist
Designs and builds GCP-based data pipelines, AI/ML models, and MLOps workflows using Dataflow, BigQuery, Kubeflow, and Python.