1 to 25 of 26 Amazon SageMaker Jobs in England

pipelines and ETL processes using state-of-the-art tools Skilled at architecting and managing secure, scalable AWS environments and working experience in the data & analytics services such as Amazon EC2, AWS Lambda, AWS Fargate, Amazon ECS, Amazon EKS, Amazon S3, AWS Glue, Amazon RDS, Amazon DynamoDB, Amazon Aurora, Amazon SageMaker, Amazon Bedrock (including LLM hosting and management). Expertise in workflow orchestration tools such as Apache Airflow Experience implementing DataOps best practices and tooling, including DataOps.Live Advanced skills in data storage and management platforms like Snowflake Ability to deliver insightful analytics via business intelligence tools such as Power BI Full-stack development experience: backend (Node.js, Python), frontend (ReactJS … Demonstrated experience designing and implementing Generative AI solutions (chatbots, digital assistants, content generation, etc.) Hands-on implementation and operation of AI/ML models with services like Amazon SageMaker Advanced proficiency in Python and related AI/ML productivity libraries Expertise in SQL and NoSQL database technologies Skills Python AWS Gen AI Job Title: Technical Lead Location: Cambridge More ❯

scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯

scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯

scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯

scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯

scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯

ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

that break down complex tasks into actionable steps. Developing innovative context engineering strategies (e.g., retrieval-augmented generation, dynamic context construction, memory optimisation). Select, benchmark, and host LLMs on Amazon SageMaker or EKS , comparing and optimising models to ensure agentic systems are fast, accurate, and cost-effective. Select, fine-tune, and adapt LLMs to meet specific objectives. Enhancing More ❯

Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional More ❯

services. Hands on experience with DevOps and engineering tools (GitLab, GitHub, Azure DevOps, Docker, Kubernetes). Proficiency with AI/ML and MLOps platforms (Databricks, Google Cloud Vertex AI, SageMaker). Familiarity with generative AI technologies and frameworks (OpenAI, Google Gemini, Hugging Face Transformers). Demonstrated success in developing and executing product strategies. Ability to lead and inspire cross More ❯

Looking For Must Have Practical experience deploying ML models into production environments Strong Python development skills and understanding of ML model structures Familiarity with tools such as MLflow, Airflow, SageMaker, or Vertex AI Understanding of CI/CD concepts and basic infrastructure automation Ability to write well-tested, maintainable, and modular code Strong collaboration skills and a growth mindset More ❯

HIPAA) Excellent communication, client engagement, and workshop facilitation skills Proven ability to work in matrix environments across global teams Desired skills Exposure to AI platforms like Azure AI, AWS SageMaker, Google Vertex AI Knowledge of PoC packaging and offer development for enterprise clients Experience Experience working with AI CoEs or global delivery teams Benefits Collaborative working environment - we stand More ❯

integration. Familiarity with CI/CD pipelines and modern DevOps workflows. Understanding of authentication, authorization, and web security best practices. Nice-to-haves: Experience deploying ML models using AWS Sagemaker, Hugging Face, or Replicate . Familiarity with WebGL, THREE.js , or other 3D graphics frameworks. Interest in AI, generative models, and spatial computing . More ❯

years experience AWS cloud and AWS services such as Redshift, DMS, RDS, Glue, S3, Athena, Lambda Experience in designing and managing a data warehouse Experience with AWS Bedrock, Sagemaker and PowerBI desirable Strong capability with SQL in both MySQL and Postgresql flavours About You A self-starter looking to make a positive impact in a rapidly evolving environment Ability More ❯

Claude, Gemini, Mistral, LLaMA, Cohere). Experiment with advanced prompting techniques; Chain-of-Thought, ReAct, Tree-of-Thoughts, and more. Deploy AI/ML pipelines using Azure ML, AWS SageMaker, Vertex AI, or Databricks. Integrate LLMs into production apps using LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices for scalable AI deployment. Use AI-powered dev tools like … related field. Tech Stack LLMs: GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch More ❯

technologies based on client delivery experience and research 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 AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG More ❯

Senior Machine Learning Engineer page is loaded Senior Machine Learning Engineer Apply locations London, UK time type Full time posted on Posted 5 Days Ago job requisition id R15074 Job Title Senior Machine Learning Engineer Job Description Here at UnderwriteMe More ❯

from strategic planning through to pre-production deployment and optimisation Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams Partner with customers to translate business challenges into measurable ML … candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most … software development life cycle (sdlc) and agile/iterative methodologies Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We More ❯

Inside IR35 1-2 days in London office We need a Lead data engineer who has hands on experience as a Data Architect: You musty have in: AWS Glue Sagemaker Architect data platforms while having hands on experience Please send me copy of your job CV if you're interested More ❯

Inside IR35 1-2 days in London office We need a Lead data engineer who has hands on experience as a Data Architect: You musty have in: AWS Glue Sagemaker Architect data platforms while having hands on experience Please send me copy of your job CV if you're interested More ❯