1 to 25 of 102 Amazon SageMaker Jobs in England

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 ❯

Senior Delivery Consultant -Data Analytics & GenAI, AWS Professional Services Public Sector Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Data Analytics and 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 … decisions and desired customer outcomes. 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 ❯

Job ID: Amazon Web Services Australia Pty Ltd Are you a Cloud Architect with GenAI experience? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake and Data Engineering experience? Do you like to solve the most complex and high scale (billions+ records) data challenges in the world today? Do you like leading … 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: 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 solutions that often span More ❯

Delivery Consultant - Data Analytics & GenAI, AWS Professional Services Public Sector Job ID: Amazon Web Services Australia Pty Ltd Are you a Data Analytics and GenAI specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you like to solve the most complex and high scale (billions+ … decisions and desired customer outcomes. 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: 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 solutions that often span More ❯

Delivery Consultant - Machine Learning (GenAI), ProServe SDT North Job ID: Amazon Web Services EMEA SARL, Dutch Branch AWS Professional Services is a unique organization. Our customers are most-advanced companies in the world. We build for them world-class, cloud-native IT solutions to solve real business problems and we help them get business outcomes with AWS. Our projects … are often unique, one-of-a-kind endeavors that no one ever has done before. At Amazon Web Services (AWS), we are helping large enterprises build AI solutions on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. AWS Professional Services works together with AWS customers to address … AI solutions with our customers. You will take advantage of the global scale, elasticity, automation and high-availability features of the AWS platform. You will build customer solutions with Amazon SageMaker, Amazon Bedrock, Amazon Elastic Compute (EC2), Amazon Data Pipeline, Amazon S3, Glue, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon More ❯

Software Development Engineer II, AWS SageMaker Training AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization … specialized security solutions for their cloud services. At AWS AI, we want to make it easy for our customers to train their deep learning workload in the cloud. With Amazon SageMaker Training, we are building customer-facing services to empower data scientists and software engineers in their deep learning endeavors. As our customers rapidly adopt LLMs and Generative … that's optimized for LLMs and distributed training.At AWS AI, we want to make it easy for our customers to train their deep learning workload in the cloud. With Amazon SageMaker Training, we are building customer-facing services to empower data scientists and software engineers in their deep learning endeavors. As our customers rapidly adopt LLMs and Generative More ❯

you will be responsible for driving strategy, top line revenue growth and overall end customer adoption of our comprehensive GenAI/ML solutions. AI/ML services such as Amazon Nova, Amazon SageMaker, Amazon Bedrock, and our generative AI offerings. You will lead a senior go-to-market team across 100+ countries in EMEA, leveraging sales … on thinking big, delivering exceptional results for our customers, and working across AWS as to build the future of AI and cloud computing. This position is part of the Amazon Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to 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 ❯

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 … and orchestration approaches Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools Experience building generative AI applications on … AWS using services such as Amazon Bedrock and Amazon SageMaker 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 value your passion to discover, invent, simplify and build. Protecting your privacy and the security of More ❯

scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark More ❯

ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end More ❯

XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML and AI services (SageMaker, Azure ML, Vertex AI) Knowledge of MLOps tools including Docker, MLflow, Kubeflow, or similar platforms Experience with version control (Git) and collaborative development practices Excellent analytical thinking and problem More ❯

for data insights Data Bricks/Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark More ❯

Strong understanding of statistical analysis, machine learning, and predictive modelling techniques. Proficiency in Python and SQL programming languages. Proficiency with at least one cloud-based ML platform, such as SageMaker, Vertex AI or Azure Machine Learning Studio. Good knowledge of DevOps practices and tools (e.g.: Git, Docker, Kubernetes). Familiarity with AI platforms and frameworks such as LangChain, Llamaindex More ❯

potential iterations which may drive improved model reliability and accuracy. Develop a testing framework and test model quality Experience with deployment to production, using standard tools including GitHub, Jenkins, Sagemaker, Docker etc Advanced programming skills in SQL, SAS (desired), Python, and the ability to write production-level code Familiarity with the most standard Python libraries used in ML (e.g. More ❯

classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelors degree (masters or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field What Would More ❯

for data/AI), SQL Cloud & DevOps: AWS/Azure/GCP services, CI/CD pipelines, Docker/Kubernetes AI/ML Tooling: Familiarity with cloud AI services (SageMaker, Vertex AI, Azure AI) and ML lifecycle management Data: Relational & NoSQL databases, data modelling, ETL/ELT, BI tools Strategic thinker with commercial acumen; can link technology to bottom More ❯

for data/AI), SQL Cloud & DevOps: AWS/Azure/GCP services, CI/CD pipelines, Docker/Kubernetes AI/ML Tooling: Familiarity with cloud AI services (SageMaker, Vertex AI, Azure AI) and ML lifecycle management Data: Relational & NoSQL databases, data modelling, ETL/ELT, BI tools Strategic thinker with commercial acumen; can link technology to bottom More ❯

Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. Experience working with large-scale MLOps pipelines, working with and deploying models to production services. About Us J.P. Morgan is a global leader in financial services, providing More ❯

and API design Hands on experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio) Be a lifelong learner and can demonstrate a drive to always be learning and developing your skillsets and develop the skillsets of others around you More ❯

delivery Proven track record deploying ML systems in production at scale (batch and/or real-time) Strong technical background in Python and ML engineering tooling (e.g. MLflow, Airflow, SageMaker, Vertex AI, Databricks) Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD) Ability to lead delivery in agile environmentsbalancing scope, prioritisation More ❯

Tech Skills Required: Advanced level of coding in Python for Data Science Software engineering architecture design for application with integrated Data Science solutions Jupyter server/notebooks AWS: EC2, Sagemaker, S3 Git version control SQL skills include selecting, filtering, aggregating, and joining data using core clauses, use of CTEs, window functions, subqueries, and data cleaning functions to handle more More ❯

and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow or PyTorch. Experience with cloud platforms such as AWS SageMaker or Azure Machine Learning. Ability to translate business problems into solutions. Strong communication skills; bilingualism/multilingualism is a plus. Willingness to travel (50% - national and international). Our More ❯

AI assistants and agentic tools to maximise impact. Bonus points if you’ve played with: LangGraph, AutoGen, or other agentic AI frameworks LoRA fine-tuning, RLHF, or vLLM AWS (SageMaker, EKS), Docker, or speech-to-text systems 🌟 What You Get: 100% remote role (UK or Spain) Work on real-world LLM deployments in an agile, experimental environment More ❯

AI assistants and agentic tools to maximise impact. Bonus points if you’ve played with: LangGraph, AutoGen, or other agentic AI frameworks LoRA fine-tuning, RLHF, or vLLM AWS (SageMaker, EKS), Docker, or speech-to-text systems 🌟 What You Get: 100% remote role (UK or Spain) Work on real-world LLM deployments in an agile, experimental environment More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯