5 of 5 Remote Amazon SageMaker Jobs in Berkshire

the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure More ❯

business. Tech-savvy : Proficient in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX). Strong command of cloud-native AI tooling (e.g., AWS SageMaker, GCP Vertex AI, AzureML/AzureAI, MLflow, Weights & Biases). Well-rounded Engineer : Comfortable working with version-controlled codebases, DevOps pipelines, containerisation/microservices More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

researchers, clinicians, and engineers Drive adoption of infrastructure-as-code and automation practices Technologies and tools: Machine Learning - MLOps (PyTorch/TensorFlow, HFT) AWS (SageMaker - Training, Pipelines, Endpoints) Data - AWS Glue, Lambda, Step Functions Airform Terraform, ECS Python (core language), Bash, (GO is advantageous but not strictly necessary) Required … experience in MLOps or ML infrastructure roles Deep familiarity with AWS services relevant to machine learning Proven experience deploying models into production (ideally using SageMaker) Working knowledge of infrastructure-as-code, ideally using Terraform Strong understanding of CI/CD, automation, and monitoring within ML environments Ability to work More ❯

results easily and safely. What You'll DoIn the first 6 months: Own and evolve pipelines built in Python and R (and Kedro and SageMaker) to analyse immune profiles Contribute to modelling projects that use ML to identify immune signatures of disease or treatment outcomes Support internal tooling that … with batch effect correction, signal drift, or statistical learning in low-n cohorts Exposure to knowledge management systems, ontologies, or scientific metadata AWS/SageMaker, Kedro and/or Dagster tooling or containerised workflows (Docker, CI/CD) What It’s Like to Work Here At IMU Biosciences, you More ❯