5 of 5 Permanent Amazon SageMaker Jobs in the South East

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

pipelines for training, validation and deployment. Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints. Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure. Applying strong engineering standards across cloud, DevOps and automation practices. Contributing to computer vision and broader ...

C++. The technology stack you will work with includes Linux, NVIDIA DeepStream, NVIDIA Jetson, Docker, Python, C++, GStreamer, PostgresSQL, Timescale DB, AWS Cloud, AWS SageMaker, and NoSQL(DynamoDB). What you'll need to succeed You will have strong knowledge and understanding of ML/Data Science concepts, processes … Linux/Unix shell scripting Highly Desirable Use of Continuous Integration products (Jenkins) Use of containerisation technologies Docker Stack/Kubernetes AWS and AWS SageMaker experience What you need to do now If you're interested in this role, click 'apply now' to forward an up-to-date copy ...