15 of 15 Remote Amazon SageMaker Jobs in the UK excluding London

CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent More ❯

a product-focused SaaS environment. Strong command of Python and relevant libraries for machine learning, data engineering, and automation. Experience working with AWS (e.g., SageMaker, Bedrock) and infrastructure-as-code tools like Terraform. Solid understanding of large-scale data pipelines, distributed systems, and microservice architectures. Comfortable working with LLMs More ❯

monitoring, and performance optimisation of ML systems Contribute to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required Experience: Proven track More ❯

monitoring, and performance optimisation of ML systems Contribute to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required Experience: Proven track More ❯

and fine‑tuning foundation‑model solutions; RAG patterns; prompt‑engineering & evaluation MLOps/LLMOps: CI/CD for models, feature stores, experiment tracking (MLflow, SageMaker, Azure ML, Vertex, etc.) Cloud‑Native Delivery: Building scalable AI pipelines on AWS or Azure; Terraform/IaC familiarity Python Excellence: Clean, testable code More ❯

such as Power BI and OAS. Understanding of data replication tools such as Oracle GoldenGate and AWS DMS. Knowledge of AWS Services such as SageMaker, Lambda, Step Functions, S3 etc would be an advantage. Hands on and technical understanding of complex Data Warehousing terminology. Python scripting knowledge would be More ❯

such as Power BI and OAS Understanding of data replication tools such as Oracle GoldenGate and AWS DMS Knowledge of AWS Services such as SageMaker, Lambda, Step Functions, S3 etc would be an advantage Hands on and technical understanding of complex Data Warehousing terminology. Python scripting knowledge would be More ❯

such as Power BI and OAS Understanding of data replication tools such as Oracle GoldenGate and AWS DMS Knowledge of AWS Services such as SageMaker, Lambda, Step Functions, S3 etc would be an advantage Hands on and technical understanding of complex Data Warehousing terminology. Python scripting knowledge would be More ❯

business in their Data Science, AI, and ML initiatives. Our Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. We are currently engaged on multiple data focused projects which are in various stages More ❯

business in their Data Science, AI, and ML initiatives. Our Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. We are currently engaged on multiple data focused projects which are in various stages More ❯

grow a diverse team who are geographically dispersed. Comfortable using a multi-platform stack to deliver products (Databricks, Azure ML Studio, Azure and Snowflake, SageMaker, AWS). Ability to take ownership of a broad data product-set and drive forward the delivery of new products and product features. Strong More ❯

deployed applications. Package and deploy ML models (including Hugging Face Transformers) as microservices on AWS. Build, train, and evaluate models using AWS tools like SageMaker, Bedrock, Glue, Athena, and Redshift. Develop secure APIs with Apigee and build automation pipelines using Jenkins, Maven, and more. Support the full ML lifecycle … with MLOps , from experimentation to deployment and monitoring. Strong grasp of ethical AI practices: model explainability, transparency, bias mitigation. Hands-on with AWS services (SageMaker, Glue, Redshift, Bedrock, Lambda, Fargate). Skilled in deploying and hosting microservices/APIs with Flask or FastAPI. Proficient in SQL, Git, Jupyter/… collaborating in a dynamic environment Tech Stack Languages & Frameworks: Python, R, SQL, Flask, FastAPI Tools: Hugging Face, Apigee, Jenkins, Git, RStudio, Jupyter Cloud: AWS (SageMaker, Glue, Athena, Redshift, Bedrock, ECS Fargate, Lambda) Please apply online for consideration. More ❯

Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting new positions available for Machine Learning … Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) This is your chance to contribute to an innovative, technically More ❯

You will need to login before you can apply for a job. View more categories View less categories Sector Engineering Role Manager Contract Type Permanent Hours Full Time Package Description Job Title: Engineering Manager Job Reference: 22697 Band: E Salary More ❯

Press Tab to Move to Skip to Content Link Choose how often (in days) you would like to receive job alerts by email: Software Engineering Permanent - Full Time Newcastle-upon-Tyne, GB, NE991RN London, GB, W1A 1AA Salford, GB, M50 More ❯