1 to 25 of 33 Amazon SageMaker Jobs in the UK

scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate AI capabilities ...

best practices Required Skills & Experience 1+ year hands-on experience deploying GenAI/LLM applications into production Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS Strong Python development skills with modern AI/ML libraries Practical experience using at least one LLM API Solid ...

best practices Required Skills & Experience 1+ year hands-on experience deploying GenAI/LLM applications into production Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS Strong Python development skills with modern AI/ML libraries Practical experience using at least one LLM API Solid ...

compliance (Zero Trust architectures, identity‐aware AI access, secrets management) AI/ML platforms, responsible AI practices, and model lifecycle management (MLflow, Vertex AI, SageMaker, Azure ML, Arize, Azure AI Studio) Design and operationalize enterprise‐scale GenAI and agent‐based solutions. Experience with modern AI architectures including Retrieval‐Augmented ...

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 ...

practice in Python. Familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch and TensorFlow. Experience with MLFlow, AWS SageMaker and Bedrock is preferred.Good written and oral communication skills, including the ability to communicate across business areas and increase overall knowledge across the organization. ...

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 ...

models and pipelines. Strong proficiency in Python, R, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms and ML infrastructure (AWS SageMaker, MLflow). Practical understanding of monitoring, logging, and CI/CD. Experience with LLMs, vector search, or retrieval-augmented systems. Comfortable working with structured ...

Strong Python skills and practical expertise with: scikit-learn for conventional ML and data science. PyTorch, TensorFlow, or Keras for deep learning. AWS Bedrock, SageMaker, HuggingFace, or Transformers for LLM-based solutions. CrewAI (or similar frameworks) for agentic AI projects. Pandas/NumPy for data processing and transformation. Intuition ...

Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration and Cross ...

Typescript GraphQL (Apollo Client) Fastlane SwiftUI (Apple Watch) Maestro E2E tests Backend: Serverless (AWS) Lambdas (NodeJS & Python) AWS AppSync DynamoDB, S3, SQS, SNS, EventBridge, SageMaker Snowflake All the other good stuff: Sentry GitHub Actions Intercom, Mixpanel RevenueCat App Store Connect/Play Store Google Tag Manager We follow ...

What we're looking for: Strong commercial Data Science/ML experience. Python and cloud ML platforms (GCP/Vertex AI or AWS SageMaker) Experience with NLP/LLM use cases. Ability to work autonomously and deliver business impact. Apply if you're a pragmatic ML Engineer who enjoys ...

implementation. Required Skills & Experience Deep experience architecting and scaling enterprise-grade AI/ML systems . Proven expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong command of agent frameworks , vector databases , and LLM orchestration tools . Ability to lead multi-disciplinary teams ...

retraining workflows.* Hands-on experience with model deployment and runtime management across varied environments (batch, real-time, REST, edge), using tools like MLflow, SageMaker, Databricks, or other equivalent.* Strong background in monitoring, observability, and incident response — including drift detection, fairness tracking, latency alerts, and recovery protocols.* Skilled in building ...

multiple projects and deliverables at any one time is essential Experience (Nice to have) AWS speciality certification Experience with machine learning services such as SageMaker or any of AWS AI services Knowledge of typical on‐premise environments such as hypervisor, storage and backup vendors Ability to write scripts ...

rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access — self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups Collaborate with Engineering, Design & Data Science ...

such as AWS, Azure or GCP across their multiple offerings Familiarity with AI‐specific cloud platform services, such as TogetherAI, ScaleAI, Databricks or AWS SageMaker, at least from a consumer standpoint and strong understanding of underlying technologies Demonstrated understanding of ML model architectures, training dynamics, and optimization techniques Past ...

influence engineering strategy. Proficiency inPython(with libraries likePyTorch, XGBoost, Scikit‐learn) andSQL. Strong experience with machine learning pipelines and orchestration tools such asAirflow,SageMaker Pipelines, or similar. Deep understanding of machine learning fundamentals, including experience withLarge Language Models (LLMs)and other emerging ML technologies. A track record of shipping ...

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 ...

Lead the end-to-end development and testing of a Python‐based ML platform. Cloud Infrastructure: Architect and manage ML environments specifically within AWS (SageMaker, Lambda, S3), ensuring scalable training and deployment pipelines. Data Orchestration: Develop a unified data structure for our AI platform using existing and new APIs … TensorFlow . Generative AI: Practical experience with LLM orchestration (e.g., LangChain) and vector databases for RAG workflows. Cloud & DevOps: Professional experience with AWS/SageMaker (or similar) and a strong comfort level with Linux/Unix environments. Data Engineering: Proficiency in SQL and experience preparing or scraping complex datasets ...

provide technical leadership across the full lifecycle of machine learning systems while architecting production-grade ML solutions. You will work with AWS SageMaker, lead teams on MLOps strategies, and ensure systems adhere to governance standards. This is a hands-on, technical position ideal for those with deep expertise ...

Description Principal AI + Data Architect, Agentforce and AI Ecosystem We're Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies ...

Role Summary We are seeking a Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance & Explainability) to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that … platform, including data pipelines, model training workflows, inference runtimes, and telemetry ecosystems. Lead adoption of best‐in‐class MLOps patterns, platform tooling, and AWS SageMaker capabilities across training, processing, registry, monitoring, and deployment. Partner with platform, security, and data engineering teams to implement scalable data lakehouse oriented feature architectures ...

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category: Sales About Salesforce Salesforce is the #1 AI ...

model performance, data drift, and system health to ensure reliability and availability. Support ML platforms and infrastructure on-premise or in the cloud (AWS, SageMaker), ensuring scalability and security. Collaborate with data scientists to productionise models and embed ML Ops best practices across the organisation. Ensure governance, compliance, documentation … model maintenance. Hands‐on experience with Python (and ML frameworks), containerisation (Docker/Kubernetes), CI/CD pipelines, and cloud ML services (AWS SageMaker preferred). Experience with infrastructure‐as‐code, production‐grade Linux environments, and API services (Flask/Gunicorn). Proficiency in building automated, reliable ML pipelines ...