26 to 50 of 84 Amazon SageMaker Jobs in England

into DV and undertake occasional overseas assignments • Strong team player with a proactive mindset, eager to shape new delivery teams Desirable Skills • Exposure to cloud ML platforms (e.g., AWS Sagemaker, Azure ML) • Experience deploying data/API services and microservice architectures • Previous consulting or defence/national security sector experience • Familiarity with Ansible or similar configuration management tooling Package More ❯

independently Excellent communication skills across technical and non-technical stakeholders Experience designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling CI/ More ❯

modern frameworks. Build and optimize RAG pipelines using models like GPT, Claude, or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.). Leverage GPU-based computing resources and CUDA/Nvidia for performance optimization in training and inference. Collaborate with data engineers, software developers, and product teams to … experience with PyTorch, TensorFlow, Scikit-learn, and transformer-based models. Practical knowledge of LLM integration (e.g., GPT, Claude) and RAG architecture. Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as More ❯

and development to succeed. A progressive organisation where you can really make a difference. We a great opportunity for a Data Scientist. You will have solid experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy … Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration in AWS. OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging … actionable insights. Stakeholder Collaboration: Effective communication with technical and non-technical stakeholders. Experience in cross-functional team. Data Engineering Basics: Familiarity with SQL and big data processing tools (e.g., Amazon Athena). Model Evaluation & Experimentation: A/B testing, statistical analysis, and performance metrics. Security & Compliance Awareness: Understanding of data privacy, PII handling, and compliance standards (e.g., GDPR). More ❯

value: • Cloud platform deployment on AWS or Azure • Containerisation using Docker or Kubernetes • Experience with Ansible or other configuration management tools • Exposure to machine learning platforms (Azure ML, TensorFlow, Amazon SageMaker) • Working with relational or NoSQL databases (document, graph, or RDBMS) Platform Engineer - Key Benefits: • Clear career progression within the National Security & Gov space • Flexible hybrid working & generous More ❯

TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading financial services (fintech More ❯

and optimize AWS-based data infrastructure, including S3 and Lambda, as well as Snowflake. Implement best practices for cost-efficient, secure, and scalable data processing. Enable and optimize AWS SageMaker environments for ML teams. Collaborate with ML, Data Science, and Reporting teams to ensure seamless data accessibility. Implement data pipeline monitoring, alerting, and logging to detect failures and performance More ❯

solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity More ❯

. Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort and cost, and contribute to proposal writing. Strong storytelling and presentation skills More ❯

direction across multiple teams. • Extensive experience in large scale machine learning, including building, deploying, scaling and securing ML infrastructure in cloud-native environments. • Strong experience with AWS services including SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, DynamoDB, Kafka, CloudFormation and associated technologies such as Python • Proven ability to drive cross functional technical initiatives and deliver results More ❯

communicate technical ideas through writing, visualisations, or presentations Strong organisational skills with experience in balancing multiple projects Familiarity with Posit Connect, workflow orchestration tools (e.g., Airflow), AWS services (e.g., SageMaker, Redshift), or distributed computing tools (e.g., Spark, Kafka) Experience in a media or newsroom environment Agile team experience Advanced degree in Maths, Statistics, or a related field What's More ❯

communicate technical ideas through writing, visualisations, or presentations Strong organisational skills with experience in balancing multiple projects Familiarity with Posit Connect, workflow orchestration tools (e.g., Airflow), AWS services (e.g., SageMaker, Redshift), or distributed computing tools (e.g., Spark, Kafka) Experience in a media or newsroom environment Agile team experience Advanced degree in Maths, Statistics, or a related field What's More ❯

Terraform for infrastructure management Grafana, Elasticsearch, Kibana & New Relic for metrics, logs and monitoring In the company we also use: VueJS, MySQL, Spring Boot, Apache Camel, AWS Redshift, AWS SageMaker, Pentaho, Balena, Serverless functions Winnow has adopted a hybrid working model where employees come to the office two days a week and can choose to work from home or More ❯

An understanding of AI, and AI ethics An understanding of data safety in use of Large Language Models Knowledge and experience of either AWS or Azure: AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2) Azure (azure Open AI service, Cosmos DB) Python Langgraph Neo4j/cypher Other coding languages/frameworks e.g. Java/.Net AI RAG (retrieval augmented generation More ❯

at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on More ❯

Have technical expertise in one or more of the following technology areas: NoSQL, such as DocumentDB/MongoDB RDF Graph database such as GraphDB ML/AI such as Sagemaker/Bedrock Search technologies such as SOLR or Opensearch/ElasticSearch Data pipeline engineering utilising cloud-based technologies (AWS) Write high quality clean, testable code, with a focus on More ❯

Have technical expertise in one or more of the following technology areas: NoSQL, such as DocumentDB/MongoDB RDF Graph database such as GraphDB ML/AI such as Sagemaker/Bedrock Search technologies such as SOLR or Opensearch/ElasticSearch Data pipeline engineering utilising cloud-based technologies (AWS) Write high quality clean, testable code, with a focus on More ❯

Lambda, Glue, API Gateway, Athena, CloudTrail, Aurora/RDS, SQS - Experience with Glue Crawlers, EUP, and Secrets Manager - Familiarity with Spark and Python for data engineering (desirable) - Experience with SageMaker Unified Studio (a plus More ❯

for data science and model development Excellent attention to detail and data quality Clear communication skills and ability to explain complex concepts Familiarity with cloud technologies like AWS and Sagemaker is advantageous Ability to work independently and collaboratively within a team TO BE CONSIDERED. Please either apply by clicking online or emailing me directly to . For further information More ❯

teams to translate data into action What You’ll Bring Strong hands-on data science and ML experience Expert in Python and modern data science libraries Experience with AWS SageMaker, Databricks, or similar cloud tools Strong background in supervised/unsupervised learning, statistical modelling, and model deployment Solid understanding of NLP techniques for document processing Domain experience in insurance More ❯

teams to translate data into action What You’ll Bring Strong hands-on data science and ML experience Expert in Python and modern data science libraries Experience with AWS SageMaker, Databricks, or similar cloud tools Strong background in supervised/unsupervised learning, statistical modelling, and model deployment Solid understanding of NLP techniques for document processing Domain experience in insurance More ❯

systems, management products, or business applications. Full-stack development experience with AI technologies/tools and apply it to user experiences or backend solutions. Experience with AI technologies like SageMaker, Vert.x, LangChain, Large Language Models, Prompt Engineering, DialogFlow, Python Experience with at least one of the following: Front-end technologies like React, Angular, SwiftUI (iOS), Kotlin (Android) Back-end More ❯

systems, management products, or business applications. Full-stack development experience with AI technologies/tools and apply it to user experiences or backend solutions. Experience with AI technologies like SageMaker, Vert.x, LangChain, Large Language Models, Prompt Engineering, DialogFlow, Python Experience with at least one of the following: Front-end technologies like React, Angular, SwiftUI (iOS), Kotlin (Android) Back-end More ❯

Delivery Consultant - Data Analytics and GenAI, AWS Professional Services Job ID: Amazon Web Services EMEA Dubai FZ Branch The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS … 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 … DevOps Engineer Professional) preferred - Experience with automation and scripting (e.g., Terraform, Python) and kowledge of security and compliance standards (e.g., HIPAA, GDPR) - Experience with AWS AI/ML services (SageMaker, Bedrock, Amazon Q), SQL and at least one programming language (Python, Java, Scala) - Experience in AWS analytics & Generative AI services (e.g., Redshift, EMR, Glue, Athena, QuickSight, Bedrock, Q More ❯

challenging. You have a voice here and are encouraged to use it. Your experience and career development is in your hands. We live our leadership principles every day. At Amazon, it's always "Day 1". Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the … 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 … learning or deep learning models and/or systems into production, including batch and real-time data processing - Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker - Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking. Our inclusive culture empowers Amazonians to More ❯