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AI DevOps/MLOps Engineer building and automating CI/CD pipelines for LLM and AI model deployment on Kubernetes/OpenShift, using Jenkins, Docker, Terraform, and model serving platforms for a Singapore-based bank.
Cloud Engineer focused on Azure Databricks platform infrastructure — designing and administering Azure foundations, Terraform IaC modules, Databricks workspaces, ADLS Gen2, Data Factory, networking, security, and monitoring for a global IT services client.
Data Engineer building and maintaining scalable data pipelines, warehouses, and data services on GCP (BigQuery, Airflow, Dataform/DBT, Pub/Sub, Cloud Functions) for a multi-carrier shipping SaaS platform, with an AI-augmented insights focus.
A Senior Data Engineer (ML) transforms data science prototypes into production-ready, scalable AI solutions by leading MLOps, CI/CD, and model monitoring. They collaborate with data scientists to optimize ML pipelines, ensure data quality, and champion responsible AI practices for government use.
Senior Data & AI / MLOps Engineer responsible for industrializing and deploying ML models, LLMs/AI agents, and data pipelines into production within the financial sector, using Python, PySpark, AWS, Docker, Kubernetes, and MLflow.
The Senior Operations AI Engineer will design and deploy autonomous AI systems and agentic workflows to optimize supply chain and logistics operations. The role involves hands-on development using Python, ML frameworks, and GenAI tools while providing technical leadership to the team.
Designs and deploys agentic AI systems for medical imaging, combining LLMs, RAG, knowledge graphs, and tool orchestration to solve complex healthcare workflows.
The Senior Machine Learning and Artificial Intelligence Scientist will lead the development and production deployment of advanced AI and ML solutions, including generative AI and multi-agent systems, to drive business impact. The role involves working across cloud-native architectures like Azure, Databricks, AWS, and GCP to build scalable, reliable, and governed AI products.
Designs and leads GenAI and Agentic AI solutions across multi-cloud environments, focusing on RAG, AI agents, and end-to-end architecture for data, integration, and security. Works with AWS, Azure, and GCP to build scalable, production-grade AI systems with governance and LLMOps practices.
The AI/ML Specialist will design and deploy scalable AI solutions, including Generative AI and NLP, within a banking environment. The role involves the full lifecycle of AI development, from data analysis and modeling to cloud deployment and CI/CD integration.
Design, build and optimise a Databricks-based data platform using Spark, Delta Lake, Python and SQL, with IaC tools in Azure, enabling analytics and ML across a retail technology company.
Build and maintain the AI and internal developer platforms, automating cloud resources, Kubernetes clusters, and CI/CD workflows for ML and dev teams using Azure, Terraform, and GitOps.
The Machine Learning & Data Operations Engineer will build and maintain ML/AI infrastructure to support drug discovery, focusing on model deployment, scalable inference, and robust data pipelines. The role involves managing the full lifecycle of models and data quality using technologies like Kubernetes, Python, Go, and various cloud-native tools.
Design, develop, deploy, and maintain AI/ML models on AWS GovCloud using SageMaker, Databricks, PySpark, and Delta Lake for federal government programs, ensuring compliance with NIST AI RMF, EO 14110, and FedRAMP standards.
NOTE: This is a 1-year, Fixed-Term Position. Are you an AI/GenAI engineer who loves shipping real systems? Join Stanford’s Enterprise Technology team to design, implement, and support AI solutions across university use…
Our team members are the key to our company’s success, and their health and well-being, as well as that of their families, is very important to us. We offer a comprehensive benefits package that allows our team members…
Senior Data Engineering Manager leading multiple teams at McKesson, overseeing Azure Data Platform (Data Factory, Synapse, ADLS), Databricks Lakehouse, and distributed data processing with Python, Scala, SQL, and Spark.
Mid-level Data Scientist building machine learning and applied AI solutions for clients using Python, Databricks, and cloud platforms (GCP, Azure) in a remote, Americas-collaborative role.
Hands-on Quantitative Risk Lead building and deploying production-grade Python microservices for VaR engines, derivatives pricing, and CIRO 5000 regulatory margin models, while managing a small quant team at Wealthsimple.
Senior Data Scientist owning the full ML production lifecycle—scaling deep learning models from R&D to reliable production systems, building data/feature pipelines, and establishing MLOps standards. Core stack includes Python/Go/Java, GCP (Vertex AI, BigQuery), Docker, Kubernetes, and MLflow/Kubeflow.
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