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Build and maintain scalable ML pipelines and infrastructure for AI-driven projects using Docker, Kubernetes, and cloud platforms like AWS/GCP/Azure.
Build and deploy NLP and generative AI systems—fine-tuning LLMs, RAG pipelines, and vector search—to automate document processing and decision support for a mid-market professional services firm.
Build and maintain the infrastructure and pipelines that deploy, monitor, and scale machine-learning models in production, using Docker, Kubernetes, and cloud ML platforms.
Lead the design of secure AI platforms, embedding privacy, compliance, and risk controls into ML pipelines and model deployments while aligning with regulations like PDPA.
Build and automate cloud infrastructure for AI/ML models and agents, deploying scalable pipelines on AWS/GCP/Azure with Kubernetes, CI/CD, and observability tools.
Maintains and optimizes a production AI medical-legal reporting platform on AWS EKS, focusing on stability, observability, and HIPAA compliance while improving infrastructure and workflows.
Build and deploy full-stack, cloud-based AI systems for customer support, integrating LLMs and real-time communication tech at massive scale.
Build and deploy ML models and MLOps pipelines using TensorFlow, PyTorch, and Scikit-learn to power a scalable AI product used daily by major Brazilian companies.
Build and operate the production ML/LLM platform for healthcare workflows, including training, deployment, monitoring, and compliance systems on GCP.
Build and deploy AI-powered systems like LLM apps and RAG pipelines for enterprise clients, integrating models into production while maintaining scalable data pipelines and MLOps workflows.
Lead a team to design, build, and maintain scalable data pipelines and ETL/ELT processes using big data tech like Spark and cloud platforms such as Azure or AWS.
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa. Minimum qualifications: Bachelor's degree in Engineering, Computer…
Responsibilities . Design, implement, and maintain cloud infrastructure using Terraform and IaC principles. . Build and manage AI platform environments across Azure, AWS, . Develop reusable Terraform modules and…
Design and maintain SQL-based data pipelines, build MMM models, and create client dashboards in Looker Studio/Tableau to turn raw media data into actionable insights for ad campaigns.
Build and maintain a governed, AI-ready data lakehouse (Databricks/Snowflake) that unifies SAP, POS, IoT, and unstructured data for analytics, ML, and GenAI use cases.
Build and deploy generative-AI agents and analytical models on GCP to automate business processes across finance, logistics, and engineering at a large appliance manufacturer.
Lead a regional team to design, deploy, and govern AI/ML and GenAI products like demand forecasting and document automation, using GCP Vertex AI and Python.
Build and maintain scalable data pipelines and infrastructure using GCP tools (Dataflow, Pub/Sub, BigQuery, Cloud Composer) to power analytics and decision-making for a global appliance manufacturer.
Job Description Build & optimize a high performance data platforms that powering analytics, dashboards , and AI models Pioneer team to freeing Data Scientists & Analysts team from manual engineering Salary up…
Senior DevOps engineer building AI-powered cloud platforms for a PropTech company that simplifies international real estate payments using AWS, Kubernetes, and CI/CD pipelines.
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