13 of 13 Permanent Amazon SageMaker Jobs in London

monolithic EC2-centric AWS infrastructure by making use of containers and AWS managed services. Building AI applications using AWS’ suite of AI services including Amazon Bedrock. Using multimodal LLMs to build applications that supercharge existing businesses with AI. Building data processing pipelines on AWS. Writing Terraform or CloudFormation … following: Infrastructure as code (IaC) with Terraform and/or CloudFormation Containerization of Python, NodeJS, PHP and .NET applications using Docker on either Amazon ECS, Amazon EKS or AWS Elastic Beanstalk. Building applications or workloads with Foundational Models such as OpenAI’s GPT, Anthropic Claude, Amazon Bedrock ...

orchestration tools like Kubeflow, Airflow, or Metaflow. Cloud Architecture: Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years ...

models in Python using libraries such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Experience deploying ML workloads on AWS, including services such as SageMaker, Lambda, and S3. Understanding of experiment design, evaluation techniques, and statistical reasoning. Experience taking models from experimentation into production environments. Familiarity with MLOps tooling such ...

serverless GenAI workflows for scalable, secure deployment. ML/LLM Engineering & LLMOps Work across AI/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/ ...

marketplace or matching algorithms. Exposure to flexibility markets, virtual power plants, or reconciliation/settlement processes. Experience with ML deployment frameworks (MLflow, Vertex AI, SageMaker). Knowledge of optimisation libraries such as Gurobi, OR‐Tools, or Pyomo. ...

automated testing (unit, integration, end-to-end) Ability to communicate complex technical concepts to non-technical stakeholders Nice to Have Experience with MLflow, DVC, SageMaker Workflow orchestration tools (Dagster/Airflow) Containerisation (Docker, ECS) Domain experience in transportation, airlines, operations, or network optimisation Qualifications Master’s degree in Data ...

expert should have: A strong academic background in data science, computer science, mathematics, or a related field. Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn ...

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 ...

grade AI development; proficiency in TypeScript. Frameworks: Hands-on experience using LangChain/LangGraph, LlamaIndex, PyTorch, and FastAPI Infrastructure: Experience with AWS Bedrock/SageMaker; Docker/Kubernetes for scaling agent instances. Proven experience building Retrieval-Augmented Generation (RAG) systems; Graph-RAG experience is a plus. Practical experience with ...

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. ...

pace of a scale-up. Requirements 2+ years MLOps experience Strong Python, ML engineering and deployment foundations. Hands-on experience with AWS and SageMaker (essential). MLOps best practice: MLflow, CI/CD for ML, monitoring, reproducibility. Cloud and DevOps knowledge: AWS, Docker, IaC (CDK preferred). Experience deploying ...

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 ...

runtime environments. Work closely with data engineering, platform engineering, security, MLOps, and Independent Model Monitoring (IMM) teams. Contribute to integration efforts with AWS SageMaker, model pipelines, and enterprise data platforms. Use technologies such as AWS, SageMaker, Python, Java, Kafka, Open Telemetry, and cloud-native monitoring stacks. Support governance … data platforms. Proficiency in Python, SQL, Java , and modern data processing frameworks. Experience working with cloud-based AI/ML ecosystems , particularly AWS SageMaker (required). Understanding of monitoring frameworks , observability pipelines, and dashboards. Familiarity of event-driven architectures and messaging systems (Kafka, Vert.x, or similar). Knowledge ...