51 to 75 of 80 Amazon SageMaker Jobs in the UK excluding London

APIs, and services used globally. Develop in one or more core technology areas: NoSQL (MongoDB, DocumentDB) Graph databases (GraphDB, Neo4j) Search technologies (ElasticSearch, OpenSearch, SOLR) ML/AI frameworks (SageMaker, Bedrock) Cloud-based data engineering (AWS) Build and maintain cloud-native data pipelines, ensuring data quality, accuracy, and reliability. What We’re Looking For 5+ years’ experience in software 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 ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

in AI development, governance, ethics, and integration, shaping our innovation roadmap. Additionally, you will optimize algorithms with tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud services (e.g., AWS SageMaker), including data analysis, model training, and validation. You will address issues in model accuracy, bias, and integration, complying with data privacy regulations while supporting growth. Finally, you will track … We provide a competitive package with benefits, bonuses, and equity shares to encourage ownership in our success. Our leaders have built and sold software firms and held roles at Amazon and Microsoft. The role will be based from home so if you are looking for flexible working in an grown up environment where you are trusted and given the More ❯

Argo CD . What Will Make You Stand Out Prior research or applied experience in edge AI or constrained/offline deployment scenarios. Direct experience with MLOps platforms like Sagemaker, Kubeflow, or ZenML. Proficiency in building RESTful services to expose AI pipelines. Literacy in security and governance standards (e.g., ISO 27001, NIST SSDF). Experience with advanced cloud orchestration … MLOps, Data Scientist, Artificial Intelligence, AWS, Terraform, Kubernetes, EKS, Docker, Containerisation, Python, Go, Bash, CI/CD, GitHub Actions, Argo CD, Edge AI, Offline AI, MOD Clearance, Security Clearance, Sagemaker, Kubeflow, ZenML, AI Architect, Solution Architect. More ❯

Argo CD . What Will Make You Stand Out Prior research or applied experience in edge AI or constrained/offline deployment scenarios. Direct experience with MLOps platforms like Sagemaker, Kubeflow, or ZenML. Proficiency in building RESTful services to expose AI pipelines. Literacy in security and governance standards (e.g., ISO 27001, NIST SSDF). Experience with advanced cloud orchestration … MLOps, Data Scientist, Artificial Intelligence, AWS, Terraform, Kubernetes, EKS, Docker, Containerisation, Python, Go, Bash, CI/CD, GitHub Actions, Argo CD, Edge AI, Offline AI, MOD Clearance, Security Clearance, Sagemaker, Kubeflow, ZenML, AI Architect, Solution Architect. 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 ❯

Data Scientist Hybrid Working – Local Site – 1-2 days a week on site. Financial Services Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be More ❯

Data Scientist Hybrid Working – Local Site – 1-2 days a week on site. Financial Services Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be More ❯

Data Scientist Hybrid Working – Local Site – 1-2 days a week on site. Financial Services Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering … or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset More ❯

the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams … automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud architecture Nice to Have: Video generation or computer vision experience, model compression, distributed More ❯

the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams … automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud architecture Nice to Have: Video generation or computer vision experience, model compression, distributed More ❯

the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams … automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud architecture Nice to Have: Video generation or computer vision experience, model compression, distributed More ❯

the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams … automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud architecture Nice to Have: Video generation or computer vision experience, model compression, distributed More ❯