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Build and deploy ML models to optimize healthcare copay programs and extract insights from pharmaceutical data using Python, R, and MLOps tools.
Lead the MLOps platform for autonomous-driving teams, building scalable AWS/Kubernetes pipelines with Ray, Airflow, and MLflow to train and deploy perception models in safety-critical automotive systems.
Lead the build and operation of MLOps platforms on AWS for autonomous-driving ML workloads, using Ray, Kubernetes, Airflow, and MLflow to ensure reproducible, traceable, and auditable pipelines.
Design and implement scalable MLOps/LLMOps pipelines on AWS, including SageMaker, EKS, and CI/CD, to deploy and monitor production-grade AI models for enterprise clients.
Lead the architecture and delivery of ML and GenAI platforms for JPMorganChase’s Home Lending, turning prototypes into production systems and mentoring AI engineers.
Build and deploy production-grade ML systems for pharma manufacturing, quality, and supply chain at Roche, using Python, MLOps, and AWS.
Design and deploy enterprise AI solutions on Red Hat OpenShift AI, including GenAI, agentic AI, and MLOps workflows, while advising customers and leading project teams.
This role is eligible for our hybrid work model: 2 days in-office This job posting is for an existing, currently vacant position. Staff Portfolio Release Manager Our Technology team is the backbone of our company:…
Design and implement a secure AWS GovCloud environment for a regulated software factory, modernizing CI/CD, Kubernetes, and MLOps while aligning with FedRAMP and NIST standards.
Build and maintain scalable eCommerce data pipelines using Azure Databricks, PySpark, and Delta Lake to power analytics and intelligent commerce experiences across Latin America.
Design and operate scalable eCommerce data pipelines using Azure Databricks, PySpark, and SQL to integrate high-volume platforms and deliver analytics-ready data products for Latin American markets.
Design and maintain AWS cloud infrastructure for AI/ML systems, including GPU clusters, CI/CD pipelines, and observability, while collaborating with AI engineers and data scientists.
Build evaluation and benchmarking infrastructure for an agentic AI platform at a cybersecurity company, using Python, LLM evaluation frameworks, knowledge graphs, and vector databases.
Senior Machine Learning Engineer Location: Chatswood, Sydney – hybrid working, three days per week in the office Reports to: ML Solution Manager About the opportunity We are seeking a hands-on Senior Machine Learning…
Lead a global team of engineers to build and maintain MLOps and analytics infrastructure using Kubeflow, MLFlow, and Feast, while mentoring engineers and driving team productivity.
Drive product strategy for open-source software at Canonical, collaborating with global teams to deliver Ubuntu and related solutions across AI, cloud, IoT, and enterprise markets.
Design and deploy AI/ML infrastructures and MLOps solutions on Ubuntu, Kubernetes, and cloud platforms for global enterprises, using open-source tools like Kubeflow and MLFlow.
Drive open-source product strategy at Canonical, shaping Ubuntu and adjacent offerings across AI, cloud, IoT, and enterprise verticals while collaborating with global teams.
Build and maintain open-source data, workflow, and AI/ML solutions using Python, Kubernetes, and tools like Kubeflow and Airflow for global cloud and on-prem deployments.
Drive product strategy for open-source software at Canonical, collaborating with engineering and marketing to deliver Ubuntu and related solutions across cloud, AI, IoT, and enterprise markets.
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