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Senior DevOps/MLOps Engineer designs and maintains GCP infrastructure, CI/CD pipelines, and MLOps workflows for a consultancy, advising clients on deployment architectures.
Designs and manages cloud infrastructure and CI/CD pipelines for AI/ML platforms using AWS, Docker, Kubernetes, and GitHub/GitLab, while implementing MLOps workflows.
Lead a DevOps team to build and run secure, scalable Kubernetes/OpenShift platforms with CI/CD, IaC, and observability, supporting AI/data workloads in a hybrid Azure/on-prem environment.
Senior DevOps Engineer designs and maintains cloud infrastructure using Terraform and Azure DevOps, automates MLOps workflows, and ensures high availability of AI/ML platforms across AWS and Azure.
Builds scalable FastAPI services in Python that expose data models and ML models on Databricks, integrating with Azure and MLOps tooling for a global fintech team.
Build cloud-native microservices and AI-native platforms for Ericsson’s Service Orchestration product, integrating LLMs, RAG, and AI workflows using Kubernetes, Python/Java, and AI tooling.
Build and own cloud infrastructure for an AI-driven materials discovery platform, focusing on GPU compute, CI/CD, and reproducibility to accelerate scientific breakthroughs.
Build and maintain cloud-native infrastructure for a healthcare data platform, using AWS, Kubernetes, Terraform, and CI/CD pipelines to support scalable, regulated SaaS and ML workflows.
Lead a team to architect and build a modern, scalable Azure/Databricks data platform handling industrial sensor data, while mentoring engineers and collaborating with data scientists.
Build and maintain Snowflake/Snowpark pipelines for a global lifestyle brand’s customer data platform, enabling faster, reliable access to insights for personalised interactions.
Principal Data Engineer builds and leads the AI data stack for Anaplan’s LLM and agentic systems, designing retrieval layers, vector/graph databases, and real-time GenAI features for enterprise planning workflows.
Build and deploy GenAI prototypes and RAG systems using Databricks, LangChain, and MLflow for trading and enterprise workflows.
Build and deploy AI/ML models (LLMs to classic regression) and shape the company’s GenAI strategy while bridging Data Science and MLOps in a fast-paced fintech environment.
Principal Data Engineer builds and leads AI systems at Anaplan, designing retrieval layers, RAG pipelines, and GenAI features that integrate LLMs into real-time planning workflows.
Senior role building and governing production-grade ML workflows on Databricks and Azure ML, using MLflow for tracking and CI/CD pipelines to safely move models from experimentation to production.
Build and optimize Azure-based ETL pipelines with Databricks and Spark, migrate SSIS to cloud, and design secure data lakes for analytics and reporting.
Design and deploy enterprise-scale GenAI, RAG, and agentic AI solutions for a global energy trading firm, using Azure OpenAI, Databricks, and LangChain to automate workflows and enhance decision-making.
Principal AI Data Engineer builds and deploys GenAI/AgenticAI systems on Azure and Databricks, focusing on RAG, AI agents, and scalable workflows.
Build and deploy Azure-based machine learning models using Python and AutoML, then monitor and retrain them to keep them accurate and ethical in production.
Build and maintain scalable data pipelines using Azure technologies and Databricks to help clients extract value from their data assets.
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