1 to 25 of 35 Amazon SageMaker Jobs in the UK

Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within: Microsoft Azure Google Cloud Platform (GCP) Additional experience with: Docker Kubernetes Git CI/CD Pipelines ...

Azure, ensuring ethical, legal and regulatory compliance. Hands on experience with ML tooling and infrastructure such as MLflow, Snowflake, Databricks, SageMaker or Azure Machine Learning and automation tools (e.g., Terraform, Python). Experience of CI/CD pipelines and source control systems (eg Git). Strong hands-on experience ...

resilient and cost‐effective deployment via Docker, Kubernetes (AKS/EKS/GKE), and Terraform/Bicep. Lead enterprise MLOPs initiatives using Azure ML, SageMaker, Vertex AI, MLflow, and Kubeflow, with continuous integration pipelines (GitHub Actions, Azure DevOps, Jenkins, Argo CD). Oversee monitoring and observability using Prometheus, Grafana ...

influence architecture, mentor engineers, and guide teams through complex technical decisions. Nice to have Experience with any of the following would be beneficial: AWS SageMaker, Bedrock, Lambda, ECS, EKS, Step Functions, EventBridge, CloudWatch, IAM, S3, ECR, or related services. MLflow, model registries, feature stores, model observability, drift detection ...

distributed teams Continuous learning mindset with a focus on emerging technologies and innovation Nice-to-Have Experience with AWS or GCP ML platforms (e.g., SageMaker, Vertex AI) Front‐end development (React) or backend development (.NET/C#) Commercial awareness and understanding of business value delivery #J-18808-Ljbffr ...

technologies like docker, Kubernetes, AWS EKS etc. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc. Master's degree or above in Machine learning/data science, computer science, applied mathematics ...

technologies like docker, Kubernetes, AWS EKS etc. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc. Master's degree or above in Machine learning/data science, computer science, applied mathematics ...

tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation, A/B testing and online evaluation ...

Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication and collaboration skills, with the ability to translate complex technical concepts for diverse, cross-functional stakeholders. ...

automated testing • Familiarity with containerisation technologies such as Docker and Kubernetes • Experience working with cloud AI and Machine Learning services including AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform • Strong analytical and problem-solving skills with the ability to develop practical AI solutions to complex business challenges ...

tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods and metrics. Ability to operationalize non-technical ideas into relevant research designs, features ...

agnostic engineering mindset; able to work across varied client stacks. Experience with cloud AI services and MLOps/LLMOps (e.g., Azure AI Foundry, AWS SageMaker and/or Bedrock). Strong software engineering practices: Python, APIs, containerisation, CI/CD, IaC, testing, observability and production support. Modern ML/ ...

Expertise with machine learning frameworks and data science packages (e.g., PyTorch, TensorFlow, Scikit‐Learn, NumPy, Pandas, SciPy, statsmodels). Experience deploying to AWS (e.g., SageMaker, Bedrock) and operating production workloads with attention to cost, performance, security, and scaling. Experience integrating human-in-the-loop or user feedback signals into ...

developing a growing team of Data Scientists Establishing best practice across model development, governance and MLOps Tech Stack Python | SQL | TensorFlow | PyTorch | AWS | Azure | SageMaker | NLP | LLMs | MLOps What we're looking for: Strong commercial Data Science and Machine Learning experience Experience leading teams or acting as a technical ...

offs. Real-time ML & reproducibility: A strong grasp of production inference patterns and reproducible environments (Docker, MLflow or equivalent). Cloud & tooling: AWS, plus SageMaker, Snowflake, Spark/Databricks and Kubernetes. Engineering mindset: A focus on reliability, maintainability and continuous improvement. ...

science/ML tooling – scikit, TensorFlow, hugging face, pytorch Any ML/Gen AI tooling such as Langchain, Langsmith, ML Flow, Dataiku, Data Robot, Sagemaker, Bedrock, Weights and Biases. Oauth/JWTs Two-stage remote interview process with capacity to start ASAP. ...

science/ML tooling – scikit, TensorFlow, hugging face, pytorch Any ML/Gen AI tooling such as Langchain, Langsmith, ML Flow, Dataiku, Data Robot, Sagemaker, Bedrock, Weights and Biases. Oauth/JWTs Two-stage remote interview process with capacity to start ASAP. ...

Qualifications - Knowledge of the healthcare domain and experience with applying AI to healthcare data - Experience with AWS especially in relation to ML workflows with SageMaker, ECS, serverless compute and storage such as S3 and Snowflake ...

Qualifications - Knowledge of the healthcare domain and experience with applying AI to healthcare data - Experience with AWS especially in relation to ML workflows with SageMaker, ECS, serverless compute and storage such as S3 and Snowflake ...

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 ...

This job is with Santander UK, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Senior AWS Cloud Engineer | S4 ...

including LLMs, prompt engineering, and model fine-tuning Hands-on experience with Hugging Face (model hub, Transformers, Inference API) Experience with AWS AI services (SageMaker, Bedrock, Rekognition, Comprehend, or equivalent) Track record of building and deploying intelligent chatbot or conversational AI solutions Solid grounding in Data Science — including model ...

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 ...

skills for querying structured datasets Proven experience developing and validating machine learning models Experience with ML deployment using containerisation or pipeline tools such as SageMaker or similar Strong experience with Git for version control Solid understanding of time series analysis and trend evaluation Excellent exploratory data analysis skills Desirable ...

skills for querying structured datasets Proven experience developing and validating machine learning models Experience with ML deployment using containerisation or pipeline tools such as SageMaker or similar Strong experience with Git for version control Solid understanding of time series analysis and trend evaluation Excellent exploratory data analysis skills Desirable ...