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Lead a team to build and optimize cloud-native data platforms, pipelines, and MLOps workflows for a large Philippine bank, ensuring scalability, security, and compliance.
Design and maintain cloud-native data platforms (Databricks, dbt, Kafka) for banking analytics and ML, using DataOps/MLOps practices to ensure secure, scalable pipelines.
Build and automate ML pipelines, deploy models to production, and manage cloud infrastructure using DevOps tools like Docker, Kubernetes, and CI/CD.
Build and deploy ML models that personalize content recommendations across Globo’s digital products using Python, TensorFlow/PyTorch, and cloud pipelines.
Leads a data science team to build AI-driven customer personalization and analytics for a UK retail brand, translating data into actionable insights for marketing and commercial strategy.
Location: Wokingham - Office based (hybrid working with 3+ days per week onsite may be considered) Start Day: ASAP Contract Rate: 460 per day inside IR35 Duration: 6 months initially Role Overview Our client is seeking…
Lead software engineering for cloud-native data, backend, and AI/ML systems at JPMorgan, building scalable production solutions in Python and AWS.
Designs and maintains scalable MLOps infrastructure and cloud-native data pipelines on AWS and GCP to productionize ML models with strong observability and governance.
Job Title: MLOps Platform Developer Location: London Salary: Depending on experience Job Type: Full time, Permanent This is a rare opportunity to be first in the door to continue the development of our engineering…
Design and build scalable cloud data platforms on AWS, Azure, and GCP using Snowflake, Databricks, and streaming tools to deliver real-time analytics and automated decision-making for enterprise clients.
Machine Learning & Data Analytics (Build the Business Engine) Design, build, and validate predictive models end to end - for example churn prediction, Customer Lifetime Value (LTV), and demand or behaviour…
Leads a team to build and maintain Prudential Malaysia’s data lake and enterprise data model on Azure, enabling analytics, AI, and regulatory reporting while ensuring governance and compliance.
Build AI-powered contact-center and agentic workflows using AWS, LangGraph, and vector databases, deploying scalable GenAI solutions for fintech customer engagement.
Build and deploy ML models for lending, credit risk, and portfolio performance on Azure/AWS, turning financial data into actionable insights for MA Financial Group.
Build and optimize AI/ML and data pipelines for a sensor-fusion system, focusing on real-time processing, CI/CD, and MLOps to support an autonomous team in Sydney.
Principal AI/Data Engineer designs and builds enterprise-scale data and AI solutions on Databricks and cloud platforms, while leading client engagements and translating complex tech into business value for executives.
Senior Data Engineer builds and maintains scalable ETL/ELT pipelines, data warehouses, and AI/ML platforms to create reusable datasets and enable customer-centric analytics and AI solutions.
Build and maintain data pipelines and MLOps frameworks in Azure to support healthcare customer analytics and propensity models for personalized marketing campaigns.
Build and productionize healthcare analytics pipelines on Azure, migrating legacy systems and implementing MLOps for propensity models to personalize insurance offerings.
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