1 to 25 of 149 Amazon SageMaker Jobs in England

Sr Worldwide Specialist Solutions Architect - GenAI, Amazon SageMaker Job ID: 2858333 | AWS EMEA SARL (UK Branch) Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on … Amazon Web Service (AWS)? Come join us! At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are … by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our More ❯

Associate Cloud Consultant, Data Analytics, AWS Professional Services, Private & Public Sector At Amazon Web Services (AWS), we're hiring highly technical Data Analytics consultants to collaborate with our customers and partners on key engagements. Our consultants will develop and deliver proof-of-concept projects, technical workshops, and support implementation … in their contract. Key Job Responsibilities In this role, you will work with our partners, customers and focus on our AWS offerings such as Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon SageMaker, Amazon Bedrock, Amazon Q, and Amazon … have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and More ❯

At Amazon, we are continuously striving to be the most customer-centric company in the world. AWS has been helping over one million customers in over 190 countries to deliver flexibility, scalability, and reliability across their organizations. Behind this success are exceptionally talented, bright, and driven individuals who work … and cost optimization. You will have the opportunity to help shape and deliver on a strategy to build mind share and broad use of Amazon's services (like Amazon Bedrock, Amazon Q, Amazon SageMaker, Amazon DynamoDB, Amazon S3, Amazon EC2, and Amazon … how applications and services are constructed using the AWS platform. The ideal candidate will possess customer-facing skills that will allow them to represent Amazon well within a customer's environment and drive discussions with senior personnel within the company, as well as a technical background that enables them More ❯

At Amazon, we are continuously striving to be the most customer-centric company in the world. AWS has been helping over one million customers in over 190 countries to deliver flexibility, scalability, and reliability across their organizations. Behind this success are exceptionally talented, bright, and driven individuals who work … and cost optimization. You will have the opportunity to help shape and deliver on a strategy to build mind share and broad use of Amazon's services (like Amazon Bedrock, Amazon Q, Amazon SageMaker, Amazon DynamoDB, Amazon S3, Amazon EC2, and Amazon … how applications and services are constructed using the AWS platform. The ideal candidate will possess customer-facing skills that will allow them to represent Amazon well within a customer's environment and drive discussions with senior personnel within the company, as well as a technical background that enables them More ❯

end machine learning solutions, from data annotation to model deployment, ensuring robust evaluation and performance monitoring in production. Develop and optimise NLP models using Amazon SageMaker and other AWS services, ensuring scalability and performance. Collaborate with cross-functional teams to integrate AI solutions into business workflows and enhance … relevant experience in a Machine Learning/Data Science role in a commercial capacity Software Engineering experience (min. 3+ years Python commercial development experience) Amazon Web Services (AWS) experience NLP expertise (document classification, key information extraction from unstructured data, etc) and deep understanding of document intelligence techniques. Proficiency in … developing and fine-tuning NLP models using Amazon SageMaker, with experience managing SageMaker pipelines. Strong understanding of deep learning and machine learning frameworks such as TensorFlow, PyTorch, transformers, NLTK, Hugging Face, or spaCy. Proven experience building end-to-end ML pipelines, including data annotation, data preprocessing, feature More ❯

solutions including Gen AI ensuring scalability, security, governance and cost optimization. Expert level knowledge in MLOps. Expertise in cloud-based AI platforms such as Amazon SageMaker, Amazon Bedrock, Databricks, and Kubernetes. Experience with AWS cloud infrastructure, networking, and IAM services. Proven ability to define AI capability models More ❯

System Development Engineer II- AWS, Sales Tech , Amazon - SalesTech Amazon Seller Services India offers innovative solutions to help sellers grow their online businesses. With a fast-paced, entrepreneurial work environment, you'll be at the heart of Amazon's drive to deliver cutting-edge cloud technologies. We … highly available AWS cloud infrastructure. Design, build, and optimize scalable solutions for data generation and processing, improving the quality and performance of models. Use Amazon Bedrock and Amazon SageMaker to support the development, training, tuning, and deployment of machine learning models. Collaborate with product and engineering teams More ❯

and other common CV libraries). Huggingface. Streamlit (or other alternatives). Cloud Technologies: AWS and knowledge of appropriate services within AWS (such as Sagemaker, Lambda, EC2, S3, RDS, DynamoDB). Understanding on how they can work together in a single pipeline. Experience with building pipelines within AWS for More ❯

Keras, Tensorflow, MMdetection (and other common CV libraries) Huggingface Streamlit (or other alternatives) Cloud Technologies: AWS Knowledge of appropriate services within AWS (such as Sagemaker, Lambda, EC2, S3, RDS, DynamoDB and etc) Understanding on how they can work together in a single pipeline Experience with building pipelines within AWS More ❯

using MEAN stack (MongoDB/DynamoDb/Non-Relational Database, ExpressJS, Angular, NodeJS). Expertise in AWS Cloud services (EC2, Lambda, S3, Elastic Beanstalk, SageMaker) and experience with infrastructure automation and containerisation tools (Terraform, CloudFormation, Docker). Strong background in DevOps methodologies, CI/CD pipelines (GitLab/Jenkins More ❯

SQL, Unix-based systems, git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity More ❯

Azure. Experience with business intelligence tools like Tableau or PowerBI. Experience working with LLMs. Experience working with AWS Services like EC2, RDS(Postgres), SQS, Sagemaker, MLflow, S3, API gateway, ECS. Experience in UI frameworks like VueJS is a plus. About Us FactSet creates flexible, open data and software solutions More ❯

transformers. Experience working with large-scale datasets, data augmentation, and feature extraction techniques. Proficiency in cloud computing services for AI/ML deployment (AWS SageMaker, Azure ML, GCP AI). Familiarity with MLOps practices, including model versioning, deployment, and monitoring. Strong problem-solving skills and ability to work in More ❯

tuning. Hands-on experience building and deploying production-grade GenAI applications. Proficiency in working with cloud AI platforms such as Google Vertex AI, AWS SageMaker, or Azure AI for model deployment and infrastructure management. Familiarity with multi-agent frameworks like LangGraph, CrewAI, or LangChain. Solid experience in data pipeline More ❯

tuning. Hands-on experience building and deploying production-grade GenAI applications. Proficiency in working with cloud AI platforms such as Google Vertex AI, AWS SageMaker, or Azure AI for model deployment and infrastructure management. Familiarity with multi-agent frameworks like LangGraph, CrewAI, or LangChain. Solid experience in data pipeline More ❯

3+ years of experience in machine learning operations, data engineering, or related roles. AWS Proficiency: Strong understanding of AWS services (e.g., EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management. Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. More ❯

Hands-on experience with AI/ML frameworks (Scikit-Learn, TensorFlow, Hugging Face, PyTorch). Familiarity with ML/Gen AI tools (LangChain, MLFlow, SageMaker, Bedrock, Weights & Biases). Experience with OAuth, JWT authentication mechanisms . Why Apply? Work on a cutting-edge AI/ML project with real More ❯

OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS. Solid understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks More ❯

Electrical Engineering, Computer Engineering or related field. Experience in containerization - Docker/Kubernetes. Experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.). Proven DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible More ❯

AI/ML tools and frameworks, including Python, PySpark, TensorFlow, PyTorch, Vertex AI, MLflow, and cloud-based ML platforms such as Azure ML, AWS SageMaker, and Google Cloud AI. Experience with production-scale AI/ML pipelines, including data exploration, feature engineering, model training and comparison, bias and fairness More ❯

technologies like Docker, Kubernetes, AWS EKS etc. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock, AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc. Master's degree or above in Machine learning/data science, computer science, applied mathematics More ❯

technologies like Docker, Kubernetes, AWS EKS, etc. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services (e.g., AWS Bedrock, AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage, etc.). Master's degree or above in Machine Learning/Data Science, Computer Science, Applied More ❯

e.g., Airflow). Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure, using services like AWS Bedrock, S3, SageMaker, Azure AI Search, etc. Champion ML governance by ensuring guidelines are followed, monitoring SLAs, and continuously improving the performance and reliability of AI solutions. More ❯

passion for machine learning and investing independent time towards learning, researching, and experimenting with new innovations in the field. Experience working with technologies like SageMaker, Athena/Trino, Spark, Milvus, and OpenSearch. #J-18808-Ljbffr More ❯

passion for machine learning and investing independent time towards learning, researching, and experimenting with new innovations in the field. Experience working with technologies like SageMaker, Athena/Trino, Spark, Milvus, and OpenSearch. #J-18808-Ljbffr More ❯