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Lead the design and deployment of enterprise AI platforms on Google Cloud using Vertex AI and Gemini, optimizing for scalability, security, and cost while implementing RAG, agentic solutions, and MLOps pipelines.
Design and optimize AI/ML models for automotive perception, prediction, and planning systems, including computer vision and trajectory forecasting for assisted/automated parking.
The Manager: AI Architecture is responsible for designing, governing, and evolving the organization’s end-to-end Artificial Intelligence (AI) architecture. The role ensures AI solutions are scalable, secure, ethical,…
Design and maintain cloud infrastructure and CI/CD pipelines for AI/ML systems, automating deployments and monitoring production AI workloads.
Build cloud-native AI platform services and secure APIs on Microsoft Azure to power AVEVA’s industrial software portfolio and partner ecosystem.
Assists in building and deploying AI models, analyzing data, and collaborating with teams to implement features using Python and ML algorithms.
Build C++/Python frameworks and APIs to run Vision and Generative AI models efficiently on custom AI accelerators, optimizing performance and integrating with compiler/runtime teams.
Designs and maintains cloud infrastructure and CI/CD pipelines for AI platforms, automating deployments of AI/ML and Generative AI applications on Azure and AWS using Kubernetes, Terraform, and MLOps practices.
Build and secure a scalable AI/ML platform on AWS SageMaker, EKS, and Azure DevOps to enable rapid healthcare model deployment and experimentation tracking.
Design and deploy AI/ML systems and data pipelines to turn raw data into scalable, business-impacting insights for PwC clients.
Builds and maintains ETL pipelines and data warehouses on GCP to feed AI-driven marketing systems, using Python, SQL, dbt, and Airbyte.
Principal AI Engineer builds and deploys AI systems for an education-tech suite, integrating LLMs, RAG, and agentic frameworks to power admissions assistants and internal tools while leading AI adoption across teams.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines to scale genAI across global operations.
Build and maintain scalable MLOps pipelines to deploy, monitor, and manage machine learning models in production using cloud platforms, CI/CD, and Kubernetes.
Build and scale backend services for an AI-powered healthcare training platform, integrating Python/Java with cloud infrastructure and ML pipelines to support thousands of global users.
Design and maintain scalable ETL pipelines, data warehouses, and real-time streaming solutions using SQL, Python, and cloud platforms like AWS/Azure/GCP.
Build and maintain Databricks pipelines, deploy ML models with MLflow, and create Power BI dashboards to support analytics and reporting in an AI-focused environment.
Lead Data Scientist building national-scale robotics and AI/ML pipelines on AWS/Databricks, deploying production ML models and transferring expertise to a government team.
Design and validate secure cloud and hybrid architectures, assess security gaps, and automate compliance using Azure and scripting (Python/PowerShell).
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