1 to 25 of 37 Amazon SageMaker Jobs in the UK

operating or integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacksFamiliarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed model hostingExperience with online large language model quality monitoring, including hallucination detection ...

creating pipelines that integrate seamlessly into production environments. Extensive experience in cloud environments (AWS, Azure, or GCP), including leveraging cloud-native AI tools like SageMaker, Vertex AI, or Azure ML Studio. Demonstrable expertise in creating interactive dashboards and visual analytics using tools such as Streamlit, Plotly, Dash, or D3.js. ...

/CD pipelines, model versioning, and monitoring. Comprehensive experience with cloud platforms (AWS, Azure, or GCP) and cloud native AI tools, such as SageMaker, Vertex AI, or Azure ML Studio. Ability to design and deploy cloud-based AI solutions. Proficiency in using containerization technologies (e.g., Docker) and orchestration tools ...

frameworks.Inference & serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms.MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks ...

practices including CI/CD pipelines, model versioning, and monitoring.Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio.Working knowledge of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions.Skills ...

including CI/CD pipelines, model versioning, and monitoring. Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio. Working knowledge of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable ...

tools, and raising potential risks to senior colleagues. Basic understanding of cloud platforms (AWS, Azure, or GCP); exposure to cloud-native AI tools (e.g., SageMaker, Vertex AI, Azure ML Studio) is a plus. Awareness of containerisation technologies (e.g., Docker); exposure to orchestration tools (e.g., Kubernetes) is beneficial ...

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)What we offerCulture of caring. At GlobalLogic, we prioritize a culture of caring. Across every ...

NeedMLOps experience: You've operationalised ML models in production, owning deployment, monitoring and lifecycle management.Strong programming: Production-quality, testable Python.Cloud expertise: Deep AWS knowledge (SageMaker, Lambda, ECS/EKS, Step Functions); Snowflake a plus.MLOps tooling: Experiment tracking and registries, workflow orchestration, model serving and feature stores.CI/ ...

Notebooks Strong understanding of predictive modelling and machine learning techniques Experience with NLP and Large Language Models (LLMs) Familiarity with AWS services, including S3, SageMaker and Lambda Experience or knowledge of Microsoft Fabric Understanding of the machine learning model development and deployment lifecycle Strong analytical and problem-solving abilities ...

strong positive signal. Hands-on production experience with graph neural networks, anomaly detection, or behavioural biometrics, beyond prototyping or fine-tuning. Familiarity with AWS (SageMaker, Lambda, S3, Athena) and CI/CD practices. Experience mentoring or technically guiding other data scientists. Please include a CV in English. Curious ...

development services on prominent cloud platforms such as Azure Open AI, Azure AI Foundry, Azure Search, Azure Cognitive Services, Terraform, AWS Bedrock, AWS Sagemaker, Gemini enterprise agent platform.Experience building AI applications, preferably Generative AI and LLM based apps.Experience deploying resources to the cloud via terraform and CI/ ...

understanding of model capabilities and limitations—not just using AI to generate code. Highly desirable: EdTech or Education experience Java Terraform Kubernetes LangChain, Bedrock, SageMaker or similar GenAI tooling OAuth/JWT This is an excellent opportunity to join a global organisation at the forefront of AI innovation, building ...

NumPy, Pandas, Scikit-Learn, xgboost, shap)Advanced working knowledge of SQLHands-on experience with data pipelines and ML infrastructureExperience working within AWS (ideally using Sagemaker) and/or AzureComfort working across our data stack - inc Airflow, SnowflakeExperience with version control and CI/CD practices (ideally using GitHub)Rigorous ...

production. Experience with AutoML frameworks. Strong understanding of regression, forecasting, and predictive analytics. Data engineering and pipeline development capability. AWS ML deployment experience (e.g. SageMaker, ECS, Lambda). Practical MLOps experience. Excellent stakeholder management and consulting skills. Experience mentoring data science teams. AWS-native ML tooling and cloud architecture ...

Cloud-based application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring all of you to workWe create the conditions ...

experience across both established enterprise approaches and modern data patterns, including:Cloud-native data platforms (AWS, Azure, GCP).Snowflake, Microsoft Fabric, and/or SageMaker (multi-platform experience advantageous).Data lake and lakehouse architectures.Event-driven and streaming architectures.Data Mesh and/or Data Fabric principles (applied pragmatically, not theoretically ...

project with a leading enterprise focused on deploying agentic GenAI solutions in AWS. Key responsibilities: Deploy and operationalise GenAI solutions in AWSBuild highly available SageMaker endpoints with monitoring and alertingDevelop Terraform modules for repeatable infrastructure deploymentsImplement CI/CD and MLOps best practicesProduce architecture documentation, configuration guides and operational ...

ability to present complex information through clear and compelling data visualisations, ideally using Tableau Experience of cloud-based data science technologies, ideally including AWS SageMaker, AWS Bedrock and Snowflake , would be highly desirable A passion for continuous learning and staying up to date with emerging data science tools, technologies ...

learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC). Experience developing LLM or Generative … agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing technologies such as Spark or Dask. Experience working within regulated or highly secure environments. ...

models influence real lending decisions and commercial outcomes Experience deploying and maintaining models within production environments Strong Python, SQL and AWS experience (particularly SageMaker and Lambda) Comfortable working in a fast-moving, hands-on environment with high ownership Excellent communication skills with both technical and business stakeholders What ...

strong expertise in SQL and Python being desirable. We're utilising the Data Science tools in the AWS Stack, so a good understanding of Sagemaker, Bedrock, and AWS Cloud Components would be highly desirable. Snowflake is our Central Data Platform, of which some experience would be desirable. Demonstrable experience ...

without a long re-orientation each time. Desirable Direct pricing or revenue management experience in live entertainment or ticketing specifically. AWS ML stack experience (SageMaker in particular), or a demonstrated fast translation from an equivalent platform. Experience with seat-map or other inventory-constrained demand modelling. Exposure ...

technical standards and reusable patterns. Experience setting technical direction and influencing engineering practices across teams. Hands‐on experience with cloud ML platforms (e.g., AWS SageMaker) and orchestration tools (e.g., Airflow, Step Functions) Strong communication skills and the ability to collaborate across Data Science, Engineering, and Data Platforms. ...

/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS Sagemaker , MLflow, Azure ML. End-end custom Sagemaker pipelines for recommendation systemsDesign and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection … chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hostedDesign and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs Build evaluation pipelines: offline IR metrics (NDCG ...