14 of 14 Permanent Amazon SageMaker Jobs in London

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Good understanding of supervised and unsupervised learning and how to choose/apply the right model to a business problem. Familiarity with AWS (e.g. SageMaker, Lambda and related data tools). Willing to develop basic–intermediate backend skills (Python with Django, Go) to support model deployment and integration. Familiar ...

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 ...

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 ...

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 ...

with PyTorch or TensorFlow - Experience training and serving models at scale (deep learning, LLMs, or classical ML) - Hands-on with cloud ML infrastructure (AWS Sagemaker, GCP Vertex, Databricks, or similar) - Strong software engineering fundamentals (testing, code review, system design) - Track record of shipping ML systems that delivered measurable business ...

with PyTorch or TensorFlow - Experience training and serving models at scale (deep learning, LLMs, or classical ML) - Hands-on with cloud ML infrastructure (AWS Sagemaker, GCP Vertex, Databricks, or similar) - Strong software engineering fundamentals (testing, code review, system design) - Track record of shipping ML systems that delivered measurable business ...

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 ...

We’re looking for a Data Engineer to join a fast-growing UK startup that’s reshaping how the hospitality industry manages staffing and operations through a data‐driven platform. You’ll play a key ...