14 of 14 Permanent Amazon SageMaker Jobs in the UK excluding London

TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow). Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++). Strong understanding of cloud ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployments (Kubernetes, Docker). Hands-on experience with data and model pipelines (feature stores, registries, distributed training, inference scaling). Knowledge of More ❯

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

model development, validation, deployment, monitoring, and maintenance Awesome If You: Have experience in the energy sector or understanding of energy systems and operations Have practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.) Have experience with infrastructure as code tools (Terraform, CloudFormation) Have experience with Apache Kafka and real-time streaming frameworks Are familiar with observability principles such More ❯

years of experience in AWS & Terraform, Jenkins, Cloudformation or any other IAAC . Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting etc). Strong hands-on More ❯

version control, CI/CD, and collaboration. • Strong coding background in Python and PySpark. • Hands-on experience with the following AWS services: o S3, Lambda, Glue, Step Functions, Athena, SageMaker, VPC, ECS, IAM, KMS • Proficiency in CloudFormation for infrastructure automation. • Experience with unit testing frameworks and best practices. • Familiarity with GitLab for source control and CI/CD ABOUT More ❯

ahead of the curve in Generative AI, ML infrastructure, and cloud-native tooling Tech Stack Programming: Python (Java familiarity is a plus) AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more On-Prem: Managed Kubernetes Platform and Hadoop ecosystem Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily to optimize strategies More ❯

required to contribute: Years of overall Data and Analytics experience with 2. Minimum 10+ years in AWS data platform including AWS S3, AWS Glue, AWS Redshift, AWS Athena, AWS Sagemaker, AWS Quicksight and AWS MLOPS 3. Snowflake DWH architecture, Snowflake Data Sharing, Snowpipe, Polaris catalog and data governance (meta data/business catalogs). 4. Knowledge of at least More ❯

A team-led hybrid working arrangement is in place. About you To be successful in this role it’s essential you have: Extensive experience with AWS (S3, Glue, Redshift, SageMaker) Experience of building and automating data pipelines in finance The ability to demonstrate, automate and manage data systems so they run smoothly and can grow easily. Familiarity with Docker More ❯

APIs, and services used globally. Develop in one or more core technology areas: NoSQL (MongoDB, DocumentDB) Graph databases (GraphDB, Neo4j) Search technologies (ElasticSearch, OpenSearch, SOLR) ML/AI frameworks (SageMaker, Bedrock) Cloud-based data engineering (AWS) Build and maintain cloud-native data pipelines, ensuring data quality, accuracy, and reliability. What We're Looking For 5+ years' experience in software More ❯

from strategic planning through to pre-production deployment and optimisation Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams Partner with customers to translate business challenges into measurable ML … 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 … software development life cycle (sdlc) and agile/iterative methodologies Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet 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 More ❯

Support proposal writing, solution direction, pricing, and costing. Define and implement data governance, security, and compliance strategies. Work hands-on with AWS services such as Redshift, Glue, Lake Formation, SageMaker, Athena, and more. Contribute to pre-sales activities and client bid responses. Mentor junior team members and contribute to internal capability building. Your Skills and Experience Required Skills & Experience … Proven experience in AWS cloud architecture, particularly in data and analytics. Strong hands-on expertise with AWS services (e.g. Redshift, Glue, Lake Formation, SageMaker). Experience designing scalable data platforms, including data lakes, lakehouses, and real-time analytics. Demonstrated success in data modernisation projects, including migration from on-premise to cloud-native platforms. Knowledge of automation tooling (e.g., CI 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 ❯

Job ID: Amazon Development Centre (Scotland) Limited Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people … of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly … the right time. You'll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the More ❯