14 of 14 Permanent Amazon SageMaker Jobs in London

with the expectation to be in the London office 1-2 times per week. Key Responsibilities Deploy ML models as real-time endpoints using Amazon SageMaker * Build and manage batch inference pipelines * Implement CI/CD workflows for ML using Git-based processes * Containerize applications using Docker * Monitor … CloudWatch * Automate data pipelines and feature workflows using Python & SQL * Ensure secure access and governance using AWS IAM and best practices Core AWS Stack Amazon SageMaker | Amazon S3 | Amazon Redshift | AWS Lambda | Amazon CloudWatch | AWS IAM What We're Looking For Strong hands-on experience ...

with the expectation to be in the London office 1-2 times per week. Key Responsibilities Deploy ML models as real-time endpoints using Amazon SageMaker * Build and manage batch inference pipelines * Implement CI/CD workflows for ML using Git-based processes * Containerize applications using Docker * Monitor … CloudWatch * Automate data pipelines and feature workflows using Python & SQL * Ensure secure access and governance using AWS IAM and best practices Core AWS Stack Amazon SageMaker | Amazon S3 | Amazon Redshift | AWS Lambda | Amazon CloudWatch | AWS IAM What We're Looking For Strong hands-on experience ...

record building and maintaining CI/CD pipelines (GitHub Actions, CircleCI, Jenkins, GitLab CI) • Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments) • Proficiency in scripting and automation (Python, Bash, Go) • Strong experience with monitoring and observability tools (CloudWatch, Prometheus, Grafana, Datadog, Sentry ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative AI initiatives using Hugging Face and open-source models Collaborate with data engineers, architects and stakeholders to deliver ...

with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/GCP) Experience in MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, etc.) API development experience Techno-Functional Capabilities Ability to translate business requirements into technical AI designs Strong solution architecture capability Experience designing ...

more cloud platforms or third-party technologies such as Google PaLM and Vertex AI, Azure OpenAI Services and Azure ML, AWS Bedrock and SageMaker, Dataiku, Databricks, Snowflake Snowpark and Snowflake Cortex, and DataRobot. Experience architecting scalable, high-performance, and cost-optimised AI and ML solutions using serverless technologies, containerised ...

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 ...

endpoints Key details: • Salary: £80,000–£110,000 + discretionary bonus • Working: Hybrid, 3 days per week in London • Stack: Python, MLflow, AWS (SageMaker), CDK, Docker • Visa: Cannot sponsor Interested? Please apply below. ...

data processing, and feature engineering experience. Strong statistical and analytical capabilities. Experience in start-up or scale-up environments. Desirable MLOps tools (MLflow, Kubeflow, Sagemaker, etc.) Experience in PropTech or property data. Cloud experience (AWS/GCP/Azure). Docker/Kubernetes, CI/CD, and event-driven ...

Frameworks: Hands-on experience with some of the following LangChain/LangGraph, LlamaIndex, PyTorch , and FastAPI . Modern Infrastructure: Experience with AWS Bedrock/SageMaker and using Docker/Kubernetes to scale agent instances. RAG Expertise: Proven experience building RAG systems; experience with Graph-RAG (e.g., Neo4j ...

intersection of modelling, engineering, and intelligent automation. 🌐 What You’ll Do 🧠 Model Development & AI Systems Design Design and train predictive models using AWS SageMaker Develop LLM-powered systems via AWS Bedrock (including Claude integration) Build RAG pipelines combining structured and unstructured data Develop evaluation frameworks for accuracy, bias … powered decision layers into enterprise processes Design human-in-the-loop feedback systems to improve performance ☁️ AWS ML Infrastructure Deploy and manage models using SageMaker (training, endpoints, pipelines) Leverage Bedrock for foundation model access Implement serverless inference with Lambda & API Gateway Utilise S3, Glue, Athena for data processing Implement ...

best practices for AI/ML implementation and data analysis. Job Requirements: Advanced proficiency in Machine Learning and Data Science. Intermediate proficiency in Amazon Sagemaker. Experience with Retrieval-Augmented Generation, Software Development Life Cycle, and Model Context Protocol. Strong problem-solving skills and the ability to contribute ...

machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration skills, and a results-driven mindset Role responsibilities: Build … tune, and maintain predictive and ML models using AWS SageMaker Analyse large datasets and perform feature engineering to improve model performance Run experiments, test hypotheses, and optimise models for accuracy and value Monitor model performance and manage retraining over time Collaborate with Data Engineers, BI Developers, and Analysts ...