3 of 3 Amazon SageMaker Jobs in West London

deploying Machine Learning models using Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … . Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments to enterprise ready architectures, balancing speed ...

ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration). There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this. You will also be responsible for MLOps … Lead, managing teams of 5+, owning end-to-end technical delivery Proficiency with Python and MLflow Strong AWS/cloud-native experience ( ideally with SageMaker exposure) React frontend proficiency Docker, Kafka, and large-scale data systems (e.g. Spark) experience Strong leadership presence and senior stakeholder communication skills ...