9 of 9 Permanent Amazon SageMaker Jobs in London

Machine Learning Engineer

Hiring Organisation
Experis UK
Location
London, UK
Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure ...

Director of AI Engineering

Hiring Organisation
Anson McCade
Location
City of London, London, United Kingdom
analytics workloads Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP within an enterprise-grade environment Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and industrialised CI/CD pipelines Ensure scalable, secure deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate ...

Lead AI Architect, Associate Director - Insurance, AI&Data, Technology & Transformation

Hiring Organisation
Jobleads-UK
Location
Greater London, England, United Kingdom
across one or more CSPs or third-party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and Sagemaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot. Experience in architecting scalable, performant & cost optimized AI/ML solutions leveraging; serverless technologies, container ...

Platform Engineer

Hiring Organisation
Vallum Associates
Location
City of London, London, United Kingdom
Python and SQL skills Understanding of data platforms (e.g. Snowflake/CDP) and ingestion pipelines Exposure to AI/ML enablement frameworks (.e.g AWS SageMaker) and supporting infrastructure for model training, deployment Familiarity with modern development and deployment frameworks Experience with dbt/ELT patterns (beneficial, not core focus ...

Machine Learning Engineer

Hiring Organisation
Anson Mccade
Location
Central London, London, United Kingdom
Employment Type
Permanent, Work From Home
Salary
£65,000
deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering ...

Data Scientist & Artificial Intelligence Specialist

Hiring Organisation
Moorfields Eye Hospital NHS Foundation Trust
Location
London, EC1V2PD, United Kingdom
Salary
£66274.00 to £73496.00
mathematical representation of complex systems (e.g., differential equation modelling and mathematical programming and optimisation). Experience with cloud computing (e.g. GCP, Azure ML, AWS SageMaker), containerisation (Docker, Kubernetes), or version control (Git). Disclosure and Barring Service Check This post is subject to the Rehabilitation of Offenders Act (Exceptions ...

Senior AI/ML Engineer

Hiring Organisation
Harnham
Location
City of London, London, United Kingdom
systems (e.g. RAG, agentic workflows, NLP). Strong product and systems thinking with a practical, impact-led mindset. Nice to Have AWS experience (e.g. SageMaker, Bedrock, Lambda, S3, Redshift). Familiarity with MLOps practices. Background in adtech, media, fraud, or adversarial systems. Why Join Work on technically challenging, high ...

Solution Engineer - AI

Hiring Organisation
Anson McCade
Location
City of London, London, United Kingdom
selection, and performance trade-offs Ability to assess use case viability and business value Cloud & Technology Experience across at least two of: AWS (Bedrock, SageMaker) Azure (Azure ML, Azure OpenAI) GCP (Vertex AI) OpenAI ecosystem Plus: Understanding of data engineering and big data concepts Awareness of cloud security, scalability ...

Data Catalog Product VP

Hiring Organisation
Jobleads-UK
Location
Greater London, England, United Kingdom
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 ...