1 to 25 of 27 Amazon SageMaker Jobs in the UK

including model hosting, request routing, continuous batching, and KV-cache optimization Deploy, host, and lifecycle-manage open-source and proprietary LLMs on Amazon EKS and Amazon SageMaker, as well as on-prem and local GPU clusters, using reproducible infrastructure as code and continuous delivery pipelines Implement observability … experience operating LLM inference servers such as vLLM and llm-d (or directly equivalent serving stacks) Hands-on experience hosting and serving LLMs on Amazon EKS and/or Amazon SageMaker, and on local GPU infrastructure Knowledge of LLM reliability and risk considerations, including latency/throughput ...

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

deploying Machine Learning models using Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge ...

/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 ...

Retrieval-Augmented Generation (RAG) AI Agents and Agentic AI Multi-agent systems Voice AI Speech-to-text/text-to-speech ElevenLabs AWS Bedrock Amazon SageMaker Google Cloud Platform (GCP) Vertex AI Python FastAPI/APIs LangChain/LangGraph Vector databases Embeddings and semantic search Hugging Face/ ...

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 ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands-on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Join us to help shape the future of Market Operations through ...

Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI use cases, reflecting where the market ...

documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands-on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML) Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment for all of our employees ...

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 ...

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 ...

experience - S3, Lambda, EventBridge, SNS/SQS Comfortable working across TOGAF, ArchiMate, C4, UML and BPMN Hands-on with MLOps tooling and platforms - SageMaker, OpenVINO or equivalent Experience architecting data for large volumes of imagery - tiering, retention, lineage, provenance Familiar with the governance side of AI - DPIAs, model documentation ...

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. ...

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 ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS , including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools . Adaptability ...

platform technologies is essential, including: AWS cloud services SQL databases PostgreSQL Python Data cataloguing and metadata management Experience with AWS services like Glue or SageMaker is a plus, but the focus remains on governance, quality, and strategy. Ideal Candidate: We're looking for a bridge-builder between business ...

platform technologies is essential, including: AWS cloud services SQL databases PostgreSQL Python Data cataloguing and metadata management Experience with AWS services like Glue or SageMaker is a plus, but the focus remains on governance, quality, and strategy. Ideal Candidate: We're looking for a bridge-builder between business ...

Star – Strategy & GTM Craft the 3-year GCP/AWS alliance roadmap tied to ambitious ARR targets. Publish “Futurify with Google Cloud Sales/Amazon Web Services” plays. Engineer the Value – Co-Innovation & Delivery Launch Dual-Cloud Lighthouses: Deploy first-of-their-kind solutions using Vertex … Amazon Bedrock/SageMaker (AWS) within 90 days; embed agentic loops into client workflows to drive immediate "futurify" impact. Stand up Multi-Cloud Enablement: Build the engine that scales—design cross-cloud certifications, sales playbooks, and real-time ROI dashboards that accelerate the co-innovation motion for both ...

dashboards, alerting, and MS Teams integrations—and reduce incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails … operations—incident triage, runbooks, and change management—with clear guardrails, auditability, and human-in-the-loop controls. Supporting AI/ML workloads at scale: SageMaker endpoints, GPU node groups, autoscaling, and Kubernetes-based model serving. Policy-as-code (OPA) and compliance implementation across CIS, NIST, ISO 27001, with automated ...

dashboards, alerting, and MS Teams integrations—and reduce incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails … operations—incident triage, runbooks, and change management—with clear guardrails, auditability, and human-in-the-loop controls. Supporting AI/ML workloads at scale: SageMaker endpoints, GPU node groups, autoscaling, and Kubernetes-based model serving. Policy-as-code (OPA) and compliance implementation across CIS, NIST, ISO 27001, with automated ...

modernization. Engineer the Value – Co-Innovation & Delivery Launch Ecosystem Lighthouses: Lead the deployment of first-of-their-kind solutions using Vertex AI (GCP) or Amazon Bedrock/SageMaker (AWS); embed agentic loops into enterprise workflows within 90 days. Build the Enablement Engine: Stand up the programs—certifications, playbooks … Converts deep-tech architectures into board-level narratives that unlock seven-figure budgets. Tech Superpowers AI-Native Architect Liaison: Translates Vertex AI (GCP) or Amazon Bedrock/SageMaker (AWS) features into monetizable, agentic solutions that solve complex business frictions. Distributed-Data Fluent: Designs BigQuery (GCP) or Redshift ...

integration Lead architectural decisions across the ML stack, ensuring scalability, reliability, and alignment with business goals Drive the ongoing migration from MLflow to AWS SageMaker, maintaining continuity and minimising disruption Define and enforce MLOps best practices across model training, serving, monitoring, and deployment MLOps & Engineering Design and maintain scalable … data engineering, and large-scale data processing Experience with containerisation (Docker) and scalable data systems (e.g. Spark, Kafka) Nice-to-Have Experience with AWS SageMaker or similar managed ML platforms Background in safety-critical or regulated industries (aerospace, aviation, or similar) Familiarity with Kafka or event-driven architectures ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … . Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments to enterprise ready architectures, balancing speed ...

ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration). There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this. You will also be responsible for MLOps … Lead, managing teams of 5+, owning end-to-end technical delivery Proficiency with Python and MLflow Strong AWS/cloud-native experience ( ideally with SageMaker exposure) React frontend proficiency Docker, Kafka, and large-scale data systems (e.g. Spark) experience Strong leadership presence and senior stakeholder communication skills ...