17 of 17 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 ...

expertise in services such as EC2, S3, RDS, Redshift, Glue, Lambda, Athena and Kinesis. Desirable: AI/Gen AI/ML services (e.g., SageMaker, Bedrock, Lex, Comprehend, Transcribe). Desirable: Experience with architecting and implementing data pipelines, data lakes, and data warehousing solutions optimised for GenAI workloads. Strong knowledge ...

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 ...

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 ...

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/ ...

Machine Learning Architect/GenAI Architect Hands-on expertise with LLMs, RAG, LangChain, LangGraph, prompt engineering Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering ...

Architect Strong hands-on expertise with LLMs, RAG architectures, LangChain, LangGraph, and prompt engineering Deep cloud knowledge including Azure OpenAI, AWS Bedrock/SageMaker, or GCP Vertex AI Experience with Kubernetes, Docker, microservices architectures, and API integrations Proficiency in Python, MLOps, LLMOps, CI/CD pipelines, and model monitoring ...

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 ...

Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts (HLDs, solution diagrams, delivery models) Exceptional writing, storytelling, and stakeholder engagement skills ...

through research Job Qualifications We are looking for experience in the following skills and experience: 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 ...

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 ...

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 ...

Company My client are a fast-growing startup revolutionising the hospitality industry by connecting businesses with a flexible, student-powered workforce. The platform enables partners—from local pubs to multinational chains—to optimise staffing in ...