101 to 125 of 225 Amazon SageMaker Jobs in London

AI and machine learning to integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes and help lead the adoption … Thorough understanding of the needs, problems, and expectations related to Integration Platforms. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the context of data mapping, flow … pressure. Excellent communication skills and a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques Degree in Computer Science or More ❯

AI and machine learning to integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes and help lead the adoption … Thorough understanding of the needs, problems, and expectations related to Integration Platforms. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the context of data mapping, flow … pressure. Excellent communication skills and a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques Degree in Computer Science or More ❯

AI and machine learning to integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes and help lead the adoption … Thorough understanding of the needs, problems, and expectations related to Integration Platforms. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the context of data mapping, flow … pressure. Excellent communication skills and a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques Degree in Computer Science or More ❯

Responsibilities: Collaborate with cross-functional teams to understand business objectives, identify data requirements, and define analytics goals. Develop and implement data analysis strategies using AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. Design and build robust data pipelines and ETL processes to extract, transform, and load data from diverse sources … advanced statistical and machine learning techniques to perform predictive and prescriptive analyses, clustering, segmentation, and pattern recognition. Identify key metrics, develop meaningful KPIs, and build dashboards and visualisations using Amazon QuickSight to enable data-driven decision-making. Conduct exploratory data analysis to uncover trends, patterns, and insights that inform product enhancements, user behaviour, and engagement strategies. Collaborate with data … Mathematics, or a related field. 2.Proven experience as a Data Scientist, preferably in a cloud-based environment using AWS analytics services. 3.Strong proficiency in AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. 4.Solid understanding of data modelling, ETL processes, and data warehousing concepts. 5.Proficiency in statistical analysis, data mining, and More ❯

and develop data-driven solutions to support business growth. Responsibilities Work with teams to understand objectives, data needs, and analytics goals. Develop data analysis strategies using AWS services like Amazon Redshift, Athena, EMR, and QuickSight. Design data pipelines and ETL processes for diverse data sources. Apply statistical and machine learning techniques for predictive and segmentation analyses. Create dashboards and … KPIs using Amazon QuickSight for decision-making. Perform exploratory data analysis to identify trends and insights. Collaborate with data engineers on data architecture, quality, and governance in AWS. Requirements Bachelor's or master's in Computer Science, Statistics, Mathematics, or related field. Experience as a Data Scientist, especially with AWS analytics services. Proficiency in AWS tools like Redshift, Athena … analytical and problem-solving skills. Experience with social media analytics and user behavior. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and deadline management. Compensation This is an equity-only position, offering More ❯

and recommendations, shaping our data strategy to support business growth. Responsibilities Collaborate with teams to understand objectives and define analytics goals. Develop data analysis strategies using AWS services like Amazon Redshift, Athena, EMR, and QuickSight. Design and build data pipelines and ETL processes for diverse data sources. Apply statistical and machine learning techniques for predictive and segmentation analyses. Develop … KPIs and dashboards using Amazon QuickSight for decision-making. Perform exploratory data analysis to identify trends and insights. Work with data engineers to optimize data architecture, quality, and governance. Requirements Bachelor's or master's degree in Computer Science, Statistics, Mathematics, or related field. Experience as a Data Scientist, especially with AWS analytics services. Proficiency in AWS tools like … problem-solving skills. Experience with social media analytics and user behavior understanding. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services such as SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and deadline management. Compensation This is an equity-only position, offering More ❯

Business Analyst, analytics and insights, EU AMZL Capacity Planning Analytics Join to apply for the Business Analyst, analytics and insights, EU AMZL Capacity Planning Analytics role at Amazon Description The goal of Amazon Logistics (AMZL) is to build a world-class last mile operation. Amazon aims to exceed customer expectations by ensuring quick, accurate, and cost-effective … SQL for data extraction and ETL pipelines. Visualization tools experience: Quicksight, Tableau, or similar. Scripting experience: R, Python, or C++. Optional: Experience with AWS solutions like S3, Athena, Sagemaker. Amazon is an equal opportunity employer committed to diversity. We value your passion for innovation and building. Protecting your privacy is a priority; please see our Privacy Notice . If More ❯

and micro-applications to serve AI/ML models, including Hugging Face Transformers and other pre-trained architectures. Build, train, and evaluate ML models using services such as AWS SageMaker, Bedrock, Glue, Athena, Redshift, and RDS. Develop and expose secure APIs using Apigee, enabling easy access to AI functionality across the Manage the entire ML lifecycle—from training and … promoting a best- practice-first culture. Essential skills: Demonstrated experience deploying and maintaining AI/ML models in production Hands-on experience with AWS Machine Learning and Data services: SageMaker, Bedrock, Glue, Kendra, Lambda, ECS Fargate, and Redshift. Familiarity with deploying Hugging Face models (e.g., NLP, vision, and generative models) within AWS environments. Ability to develop and host microservices More ❯

tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g., Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). #J-18808-Ljbffr More ❯

mentoring practice teams. Skills & Experience Required: 13-18 years of overall Data and Analytics experience. At least 10+ years in AWS data platform including AWS S3, Glue, Redshift, Athena, Sagemaker, Quicksight, and MLOPS. Expertise in Snowflake DWH architecture, Snowpipe, Data Sharing, Polaris catalog, and data governance. Knowledge of additional technologies such as Python, Streamlit, Matillion, DBT, Atlan, Terraform, Kubernetes More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

data science teams. Ability to build and communicate complex solutions to stakeholders across different levels and disciplines. Proficiency working with modern cloud-based tools (e.g., Azure ML , Databricks , Snowflake , SageMaker , etc.). Deep knowledge of machine learning techniques including predictive modelling, pattern recognition, and optimisation. Strong stakeholder management and product ownership skills. Experience with CI/CD tools such More ❯

collaboratively across disciplines. ● Experience integrating or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a collaborative team but also work More ❯

collaboratively across disciplines. ● Experience integrating or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a collaborative team but also work More ❯

collaboratively across disciplines. ● Experience integrating or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a collaborative team but also work More ❯

re open and borderless – naturally inclusive in how you work with others. Required Skills and Experience •Knowledge of modeling tools and programming languages, e.g., Azure ML, Vortex AI AutoML, SageMaker, or Python •Excellent problem-solving, analytical, and critical thinking skills •Communication and presentation skills, with the ability to convey complex data insights to both technical and non-technical audiences More ❯

Nice to haves Experience with containers and container orchestration: Kubernetes, Docker, and/or Mesos, including lifecycle management of containers Experience working with AWS technologies such as EC2, S3, Sagemaker What do you get for all your hard work? A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles . You More ❯

objectives and performance to business stakeholders Strong analytical and problem-solving skills Ability to think creatively and insightfully about business problems Nice to have : Proficiency with Snowflake Proficiency with Amazon SageMaker Proficiency with Docker and Kubernetes The Perks We trust you, so we offer flexible working hours, as long it suits both you and your team; Physical and More ❯

Driven Design approaches 1+ years in enterprise technology professional services, in a consulting or other customer-facing delivery role AI-specific tools such as TensorFlow, Google Cloud AI Platform, Amazon SageMaker, etc Working in a number of distinct industries/verticals Success measures Within 3 months: Complete internal training on MongoDB Be connected to the broader AI-focused More ❯

will play a key role in designing and implementing AI-driven solutions, leveraging Large Models (LLMs), Generative AI, Open-Source AI tools, and AWS technologies such as Athena and SageMaker . This position requires strong technical expertise, problem-solving skills, and the ability to work collaboratively within a global AI-focused team. Key Responsibilities Develop and optimise AI and … machine learning models, with a focus on NLP and Generative AI . Design, implement, and deploy scalable AI solutions using AWS services , including Athena, SageMaker, and Lambda. Work with LLMs and Open-Source AI frameworks , ensuring model efficiency and accuracy. Collaborate with cross-functional teams to integrate AI-driven capabilities into business applications. Conduct performance optimisation and fine-tuning … ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Extensive experience in NLP and Generative AI , including working with large-scale models. Proficiency in AWS cloud computing , including Athena, SageMaker, and related AI/ML services. Experience in AI model optimisation, fine-tuning, and deployment in production environments. Strong analytical skills with the ability to solve complex AI-related More ❯

PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting new positions available for Machine Learning Engineers to join a forward … PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) This is your chance to contribute to an innovative, technically demanding project focused on developing More ❯