1 to 25 of 41 Amazon SageMaker Jobs in England

Overview Job ID: Amazon Development Center U.S., Inc. Are you a highly skilled and innovative Software Development Engineer with a passion for developing new machine learning capabilities and driving innovation to build customer-centric solutions in Amazon SageMaker AI? Are you interested to play a key role in developing software applications at AWS? We invite you to … join us and be part of making history. The Amazon SageMaker Pipelines team is seeking highly skilled and innovative Software Development Engineer to join our organization. SageMaker Pipelines provides a serverless workflow orchestration capability purpose-built for MLOps/LLMOps automation. This capability enables our customers to easily build, execute, and monitor repeatable end-to-end machine … building and maintaining capabilities within our best-in-class machine learning offering, as well as scaling those systems to support our customers' workflow orchestration automation needs. Engineers on the Amazon SageMaker Pipelines team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure SageMaker remains a best-in-class service. More ❯

Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Cloud Architect with GenAI consulting specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you have senior stakeholder engagement experience to support pre-sales and deliver consulting engagements? Do you like to solve … Vetting Agency clearance (see ). Key job responsibilities Expertise: Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon DataZone, Amazon SageMaker, Amazon Quicksight and Amazon Bedrock. Solutions: Support pre-sales and deliver technical engagements with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating consulting proposals and creating packaged data analytics service offerings. Delivery: Engagements include projects proving the use of AWS services to support new distributed computing More ❯

data pipelines and ETL processes using state-of-the-art tools. Skilled at architecting and managing secure, scalable AWS environments and working experience in 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 Details Job Title: Technical More ❯

Overview 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 solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer … robust and scalable AI solutions for business problems Interact with customers directly to understand the business problem, assist in the implementation of their ML ecosystem Leverage Foundation Models on Amazon Bedrock and Amazon SageMaker to meet performance needs Analyze large historical data to automate and optimize key processes Communicate clearly with attention to detail, translating rigorous mathematical … CV, GNN, or distributed training Ability to create compelling customer proposals and present to executives; proficient English communication in technical and business settings Preferred Qualifications Experience with AWS services (Amazon SageMaker, Amazon Bedrock, EMR, S3, EC2); AWS Certification (Solutions Architect Associate, ML Engineer Associate) preferred Knowledge of AI/ML, generative AI; hands-on prompt engineering and More ❯

Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities … Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems. Optimise model performance and scalability. Monitor and maintain deployed models, ensuring reliability and accuracy. Stay up-to-date with … research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (eg, NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD More ❯

Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities … Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems. Optimise model performance and scalability. Monitor and maintain deployed models, ensuring reliability and accuracy. Stay up-to-date with … research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD More ❯

innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. The Role The Amazon Web Services (AWS) Senior Applied AI Architect partners with customers to design and build some of the most scalable, flexible and resilient cloud architectures and solutions. AWS Applied AI … enterprise customers through your passion for educating, training, designing and building cloud solutions. As a Senior Applied AI Architect, you will use ML and Generative AI tools, such as Amazon SageMaker, Amazon Bedrock, Amazon Q and other technologies to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. You'll help … 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 More ❯

Delivery Consultant - AI/ML, Professional Services Job ID: AWS EMEA SARL (UK 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 solutions that meet their technical … solutions for business problems Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs Analyze and extract relevant information from large amounts of historical data to help automate and optimize … 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 More ❯

treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding of software engineering fundamentals: version control, code reviews, automated testing, and containerization. Familiarity with FX markets, risk management concepts, or More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … 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 … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Our inclusive culture empowers More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … 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 … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Our inclusive culture empowers More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

facing technical role such as Solutions Engineer, Sales Engineer, Developer Advocate, or Technical Consultant. You have deep experience with the AWS ecosystem and services relevant to ML, such as SageMaker, EC2, S3, IAM, and VPC. You are familiar with deep-learning frameworks like PyTorch or JAX, and libraries from the AI ecosystem like Hugging Face Transformers. You have worked More ❯

to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯

experience with cloud-native development (GCP preferred). Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying More ❯

models (ASR, diarization, TTS) or document intelligence (OCR, NER). Knowledge of ML Ops (experiment tracking, monitoring, CI/CD for ML). Familiarity with cloud AI services (AWS Sagemaker, GCP Vertex AI, Azure ML). Exposure to business process improvement or automation. If this role is of interest and you would like to learn more, please get in More ❯

About Amazon Web Services Since 2006, Amazon Web Services has been the world's most comprehensive and broadly adopted cloud. AWS has been continually expanding its services to support virtually any workload, and it now has more than 240 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT … challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Amazon Web Services came to China in 2013, and has been relentlessly investing and expanding our infrastructure and business since then. Amazon Web Services launched its China (Beijing) Region … operated by Sinnet) in September 2016 and its China (Ningxia) Region (operated by NWCD) in December 2017. In 2019, Amazon Web Services added a new region in Hong Kong, making China the only country with three Amazon Web Services regions aside from the U.S. In 2022, Amazon Web Services launched Local Zone in Taipei. Amazon Web More ❯

and Skill Requirements Required: Strong Python programming fundamentals PyTorch Docker and containerised deployments Linux & Windows 10 development experience GIT, GitHub and collaborative software development Nice-to-Haves: AWS (S3, SageMaker, Lambdas) MLOps, CI/CD processes PyTorch-Ignite TypeScript & Semantic UI React SSH and secure deployment workflows Bonus Skills: JIRA & Confluence ClearML What We Value At Hawk-Eye, our More ❯

adoption and long-term success of Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration and Cross-Functional Leadership Product Alignment More ❯

conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML: Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms (e.g., Google Vertex AI, AWS Sagemaker). Hands-on work with Generative AI, Large Language Models (LLMs), agent-based frameworks, and prompt engineering. LI-YUnleash Your PotentialWhen you join Salesforce, you'll be limitless in 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 ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯