4 of 4 Amazon SageMaker Jobs in the South East

Skills & Experience Technical Skills Strong expertise in Python for data science and ML engineering. Solid hands-on experience with AWS , including services such as Amazon SageMaker . Comfortable with software version control (Git) and collaborative workflows. Experience with experiment tracking/management tools (e.g., SageMaker Studio , MLflow ...

responsibilities: Design, develop, and implement automation solutions and AI-driven applications to optimise network control processes. Utilise AWS Bedrock, AWS Quicksuite, and AWS SageMaker, AWS Quicksuite and AWS Connect to build, deploy, and maintain scalable machine learning and automation pipelines. Collaborate with cross-functional teams, including operations, data science ...

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 ...