1 to 25 of 69 Amazon SageMaker Jobs in the UK

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 ❯

Sr 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 … 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 ❯

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 ❯

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 … business problems 2. Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem 3. Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs 4. Analyze and extract relevant information from large amounts of historical data to help automate and … 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 … business problems 2. Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem 3. Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs 4. Analyze and extract relevant information from large amounts of historical data to help automate and … 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 ❯

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 ❯

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 ❯

Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB 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 ❯

SQLAlchemy experience. Nice to have skills Experience with Machine Learning (ML): deploying and managing models, creating inference pipelines, and ML Ops practices. Knowledge of ML platforms such as Airflow, SageMaker, Kubeflow, or MLFlow. Experience with distributed computing (e.g., Spark/PySpark). Understanding of cloud ML deployment and model serving on platforms like AWS, Azure, or GCP. Experience with 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 ❯

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 ❯

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 ❯

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 ❯

Agile, and test-driven development. Docker/Kubernetes containerisation and CI/CD pipelines. Additional valued skills include: AWS implementation experience using IaC and best practices (EC2, EKS, GPUs, SageMaker, RDS). Curious engineers with good collaborative skills. Data engineering experience with frameworks like Airflow, DBT, Spark. Bachelor's degree in Computer Science, related fields, or equivalent experience. This More ❯

Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional More ❯

into DV and undertake occasional overseas assignments • Strong team player with a proactive mindset, eager to shape new delivery teams Desirable Skills • Exposure to cloud ML platforms (e.g., AWS Sagemaker, Azure ML) • Experience deploying data/API services and microservice architectures • Previous consulting or defence/national security sector experience • Familiarity with Ansible or similar configuration management tooling Package More ❯

image processing workflows, deep learning pipelines, and model evaluation. Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. What you'll be doing: Research and develop solutions to complex business problems, working with large, unstructured datasets. Apply More ❯

independently Excellent communication skills across technical and non-technical stakeholders Experience designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling CI/ More ❯

value: • Cloud platform deployment on AWS or Azure • Containerisation using Docker or Kubernetes • Experience with Ansible or other configuration management tools • Exposure to machine learning platforms (Azure ML, TensorFlow, Amazon SageMaker) • Working with relational or NoSQL databases (document, graph, or RDBMS) Platform Engineer - Key Benefits: • Clear career progression within the National Security & Gov space • Flexible hybrid working & generous More ❯

SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines) Version Control (Git): To maintain reproducible and collaborative workflows Time-Series Analysis: To assess risk trends over financial years Exploratory Data Analysis (EDA): To spot early signals More ❯

TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading financial services (fintech More ❯

and optimize AWS-based data infrastructure, including S3 and Lambda, as well as Snowflake. Implement best practices for cost-efficient, secure, and scalable data processing. Enable and optimize AWS SageMaker environments for ML teams. Collaborate with ML, Data Science, and Reporting teams to ensure seamless data accessibility. Implement data pipeline monitoring, alerting, and logging to detect failures and performance More ❯

Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI Platform, Azure ML) Ethics in Data Science and AI Person Specification: Experience supporting data science training or mentoring professionals in a data-focused capacity Strong ability to More ❯