10 of 10 Amazon SageMaker Jobs in Central London

with serving patterns (e.g., REST APIs, batch inference, event-driven) Experience with orchestration tools (e.g., Airflow, Dagster) and cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI) Ability to influence decision-making regarding infrastructure and tooling, balancing 'build vs. buy' discussions Strong knowledge of Infrastructure as Code (Terraform ...

everything that gets those models in front of a customer and keeps them running: the training and deployment infrastructure on AWS and SageMaker, reproducible and configuration-driven training runs, environments defined in code, release pipelines that make a deployment routine rather than an event, and the monitoring that tells … machine learning engineers/scientists and turn them into production services that meet our latency, cost and reliability targets. Build and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them. Make training runs reproducible and configuration-driven, so any result can be rebuilt from code. ...

Terraform, Jenkins, Cloudformation or any other IAAC. Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools. Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting ...

Technical Knowledge: Strong understanding of modern AI/ML technologies and cloud-based solutions. Tools & Platforms: Familiarity with Snowflake, Databricks, Azure AI Foundry , AWS SageMaker, and other leading platforms. Data Science Expertise: Knowledge of data science fundamentals, solution lifecycles, and MLOps methodology. Generative AI Knowledge: Experience with LLMs, neural ...

Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform Deep architectural understanding of how Data and AI are activated within Salesforce — including ...

commercially credible solutions developed. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise, Dell AI Factories) Understanding of data engineering practices (ETL, data lakes ...

leaders and translate AI capability into value. Technical depth: Experience with modern AI and ML platforms such as PyTorch, TensorFlow, Azure ML and AWS SageMaker, data architecture and pipelines, and integration with OT, SCADA or ERP systems. Familiarity with NVIDIA platforms, edge computing or robotics frameworks is a strong ...

applications. Agent orchestration, tool calling, RAG, context engineering, vector databases, event‐driven integration and human approval workflows. Deployment through Anthropic APIs and/or Amazon Bedrock or Google Cloud Vertex AI, with broader AWS, Google Cloud or Microsoft Azure experience. DevSecOps, containers, infrastructure as code, cloud security, monitoring, scaling … Experience leading engineering delivery, reviewing code, mentoring developers and converting prototypes into maintainable production services. AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB Implementation of AI/ML architectural patterns and best practices ...

driven workflows) with monitoring, versioning and CI/CD Maintain and improve an AWS-native data platform (e.g., S3, Redshift, RDS, Athena, SageMaker, Lambda) Write and optimise complex SQL for analytics, reporting, modelling and downstream BI use Build and maintain integrations with internal services and partner systems to enable … moving environment where you can have meaningful impact Nice to Have Experience with AWS services commonly used in modern data platforms (e.g., Redshift, Athena, SageMaker, Lambda) Prior experience supporting analytics and ML teams with data modelling and reliable datasets Mentoring experience (formal or informal) Package Salary ...

learning engineer to own the training and deployment infrastructure for our production ML models. You will manage the training and inference workloads on AWS SageMaker, build reproducible training runs, and monitor model performance in live hospital environments. The role emphasizes production readiness, scalable systems, and collaboration with ML scientists ...