19 of 19 Permanent Amazon SageMaker Jobs in England

record building and maintaining CI/CD pipelines (GitHub Actions, CircleCI, Jenkins, GitLab CI) • Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments) • Proficiency in scripting and automation (Python, Bash, Go) • Strong experience with monitoring and observability tools (CloudWatch, Prometheus, Grafana, Datadog, Sentry ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative AI initiatives using Hugging Face and open-source models Collaborate with data engineers, architects and stakeholders to deliver ...

more cloud platforms or third-party technologies such as Google PaLM and Vertex AI, Azure OpenAI Services and Azure ML, AWS Bedrock and SageMaker, Dataiku, Databricks, Snowflake Snowpark and Snowflake Cortex, and DataRobot. Experience architecting scalable, high-performance, and cost-optimised AI and ML solutions using serverless technologies, containerised ...

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 ...

some of the following tools; Apache Spark, Databricks, Pandas for data processing and feature engineering SQL, MongoDB for structured and unstructured data management SageMaker, Azure ML for model deployment, tracking, and monitoring. Terraform, Ansible, GitLab CI/CD, Jenkins for infrastructure automation and DevSecOps ...

Machine Learning Architect/GenAI Architect Hands-on expertise with LLMs, RAG, LangChain, LangGraph, prompt engineering Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering ...

Architect Strong hands-on expertise with LLMs, RAG architectures, LangChain, LangGraph, and prompt engineering Deep cloud knowledge including Azure OpenAI, AWS Bedrock/SageMaker, or GCP Vertex AI Experience with Kubernetes, Docker, microservices architectures, and API integrations Proficiency in Python, MLOps, LLMOps, CI/CD pipelines, and model monitoring ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...

technical audiences. Understanding of Information Governance, ethics, and AI explainability. Excellent problem-solving, organisational, and communication skills. Desirable Cloud computing (Azure ML, AWS SageMaker), APIs, Git Data engineering or DevOps awareness Familiarity with interoperability standards (FHIR, HL7, OpenEHR). Awareness of national data strategies (Data Saves Lives, PHM Framework ...

Sourcegraph & Meta. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure. Infrastructure as Code: Knowledge of IaC tools ...

Sourcegraph & Meta. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure. Infrastructure as Code: Knowledge of IaC tools ...

team-led hybrid working arrangement is in place. About you For this role youll need to have: Extensive experience with AWS (S3, Glue, Redshift, SageMaker) Experience leading and coaching individuals to provide ongoing oversight over the development of data products. Experience of building and automating data pipelines in finance ...

team-led hybrid working arrangement is in place. About you For this role youll need to have: Extensive experience with AWS (S3, Glue, Redshift, SageMaker) Experience leading and coaching individuals to provide ongoing oversight over the development of data products. Experience of building and automating data pipelines in finance ...

intersection of modelling, engineering, and intelligent automation. 🌐 What You’ll Do 🧠 Model Development & AI Systems Design Design and train predictive models using AWS SageMaker Develop LLM-powered systems via AWS Bedrock (including Claude integration) Build RAG pipelines combining structured and unstructured data Develop evaluation frameworks for accuracy, bias … powered decision layers into enterprise processes Design human-in-the-loop feedback systems to improve performance ☁️ AWS ML Infrastructure Deploy and manage models using SageMaker (training, endpoints, pipelines) Leverage Bedrock for foundation model access Implement serverless inference with Lambda & API Gateway Utilise S3, Glue, Athena for data processing Implement ...

best practices for AI/ML implementation and data analysis. Job Requirements: Advanced proficiency in Machine Learning and Data Science. Intermediate proficiency in Amazon Sagemaker. Experience with Retrieval-Augmented Generation, Software Development Life Cycle, and Model Context Protocol. Strong problem-solving skills and the ability to contribute ...

machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration skills, and a results-driven mindset Role responsibilities: Build … tune, and maintain predictive and ML models using AWS SageMaker Analyse large datasets and perform feature engineering to improve model performance Run experiments, test hypotheses, and optimise models for accuracy and value Monitor model performance and manage retraining over time Collaborate with Data Engineers, BI Developers, and Analysts ...

governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift … closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working ...

governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift … closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working ...