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Develop and automate Python-based DevOps pipelines for pipeline-inspection systems using Docker, Kubernetes, and Azure DevOps.
Build and automate scalable MLOps platforms and AI infrastructure, deploying ML pipelines on Kubernetes and cloud-native environments to support data scientists and AI engineers.
Lead a team to design, build, and deploy AI models for Saudi Aramco’s business units, turning data into predictive insights and production-ready solutions.
Build and deploy AI models to improve player experience in Kammelna Games, including churn prediction and personalization, using Python, ML frameworks, and MLOps tools.
Build production-grade AI tools and data pipelines for the Group CEO, turning executive problems into reliable LLM-enabled workflows and decision-support systems while aligning with maritime and trading operations.
Build, deploy, and maintain production-grade ML models and MLOps pipelines using Python, Docker, Kubernetes, and cloud platforms.
Build and operate the cloud infrastructure, CI/CD pipelines, and Kubernetes clusters that power Blitzy’s AI agent platform, enabling autonomous software development at scale.
Designs and maintains cloud infrastructure and CI/CD pipelines to deploy and operate AI models in production, collaborating with AI teams and automating ML workflows.
Build and maintain AI infrastructure for model hosting, training, and serving at scale using Kubernetes, cloud platforms, and GPU orchestration.
Build and productionise ML models for an e-commerce platform, using Python, TensorFlow/PyTorch, and cloud pipelines to improve product recommendations and business decisions.
Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as…
Build and maintain scalable data pipelines to process complex biological datasets for training AI foundation models in drug discovery and healthcare.
Build, deploy, and monitor ML/AI models and GenAI systems using Python, TensorFlow, PyTorch, and MLOps tooling like MLflow and Kubernetes.
Lead the design and deployment of advanced AI models, including LLMs and multimodal systems, using deep learning and statistical methods to solve complex business and research challenges.
Build and operate sovereign AI infrastructure for government clients, deploying GPU clusters in air-gapped data centers and cloud (Azure/GCP) using Kubernetes, GitOps, and offline artifact pipelines.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build and maintain AI-powered data pipelines and infrastructure for document automation, deploying LLM agents and ensuring scalable, reliable AI systems in production.
Build and maintain a self-serve data platform for a large classifieds marketplace, owning batch and streaming pipelines, lake management, and APIs that power analytics and ML workloads using Databricks, AWS, Spark, Python, Kafka, and Airflow.
Build and maintain scalable data pipelines on Google Cloud using BigQuery, Cloud Storage, and Kubeflow, while automating infrastructure with Terraform, Kubernetes, and CI/CD tools.
Lead a team building AI-powered data and ML systems for eBay sellers, including pricing intelligence, demand recommendations, and seller analytics using Java/Kotlin, Python, Spark/Scala, and LLMs.
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