Join the Prodapt team in building a unified, cloud-native environment for scalable machine learning inferencing. You will help design, develop, and optimize robust workflows that empower data scientists and engineers to efficiently deploy, serve, and monitor ML models at scale, supporting both real-time and batch inference use cases.
ResponsibilitiesDevelop, maintain, and enhance model deployment workflows using Seldon, Docker, and Kubernetes for scalable inferencing.
Build and optimize REST and gRPC endpoints for serving ML models, ensuring secure and reliable access from internal tools and pipelines.
Integrate with AI Hub for unified model registration, endpoint management, and monitoring.
Support both online (real-time) and offline (batch) inference, leveraging batch inference capabilities.
Manage container images and model artifacts using Docker Hub, Artifact Registry, and Google Cloud Storage.
Implement and maintain CI/CD pipelines for automated model deployment and endpoint promotion. Ensure robust security, compliance, and governance, including role-based access control and audit logging. Collaborate with data scientists, ML engineers, and platform teams to deliver production-grade inferencing solutions. Participate in code reviews, architecture discussions, and continuous improvement of the inferencing platform.

Keyskills: continuous integration python cd tools ci / cd tools ml kubernetes rest technical leadership machine learning grpc docker spring boot java hub gcp devops jenkins debugging troubleshooting model development code review api aws application deployment
Prodapt is a two-decade-old consulting & managed services provider, singularly focused on the telecom/DSP (digital service provider) ecosystem that helps clients transform their IT, products, operations, and networks to meet their strategic objectives. Prodapt provides end-to-end IT/software arc...