22 of 22 Amazon SageMaker Jobs in the UK excluding London

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 (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 ❯

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 ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to 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 ❯

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 ❯

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 ❯

and ML engineers to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data … software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of ML Ops practices, including monitoring, scaling, and retraining More ❯

and regulatory requirements Required Expertise: Extensive ML Ops/ML Engineering experience, particularly in assurance, governance, and monitoring Hands-on knowledge of ML Ops platforms and tools (Kubeflow, MLflow, SageMaker, Azure ML, or equivalent) Proven ability to deploy and maintain AI solutions in regulated or complex operational settings Strong grounding in responsible AI practices, including explainability and fairness Experience More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you'll be building production … image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy models at scale using AWS - including Lambda, EC2, S3, and SageMaker Meet with enterprise clients to explore problems, present ideas, and share results Prototype fast, test often, and get working solutions into the hands of users Work cross-functionally with More ❯

Description 9 Months Fixed Term Contract The Data Science role is responsible for using Data Science and modelling techniques to address critical questions for both the business and our customers. This includes understanding the challenges our customers face with regards More ❯

Description 9 Months Fixed Term Contract The Data Science role is responsible for using Data Science and modelling techniques to address critical questions for both the business and our customers. This includes understanding the challenges our customers face with regards More ❯

facing role blends data analyst and data engineer skills, including requirement gathering, stakeholder communication, and delivering robust data solutions. Hands-on experience with Power BI, Sisense, Quicksight, and AWS (Sagemaker Unified Studio preferred) is highly desirable. Offering a competitive salary, performance-based bonuses, and fully flexible remote working, this is a fantastic opportunity to shape and lead analytics projects … analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable 2-5 years' client More ❯