12 of 12 Amazon SageMaker Jobs in the North of England

a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience with More ❯

a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience with More ❯

a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience with More ❯

on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices. Required/Primary Skills: AWS Data Engineering ML Engineering ML-Ops ECS, Sagemaker Gitlab Jenkins CI/CD AI Lifecycle Experience in front-end development (HTML, Stream-lit, Flask Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

with the organisation's existing team to support the delivery of one of the organisation's key strategic initiatives. Experience required: AWS Data/ML Engineering & ML Ops (ECS, Sagemaker) CI/CD pipelines (GitLab, Jenkins) Python, PySpark & Big Data ecosystems AI/ML lifecycle, deployment & monitoring MLOps tooling (MLflow, Airflow, Docker, Kubernetes) Front-end exposure (HTML, Flask, Streamlit More ❯

engineers. This role will require the software and dev ops capabilities of an ML Ops engineer to build ML and CI-CD pipelines, proficiency in Infrastructure as Code and Sagemaker pipelines combined with Data Engineering capabilities. Role Summary: Working across projects within the business and the wider industry through the organisation's parent company, you will have responsibility for … and scripting in Bash and Python. Strong experience with AWS infrastructure with proficiency in the services such as: S3, EC2, Lambda functions, Cloud Formation, Athena, Dynamo DB, Code Commit, SageMaker, etc. Strong experience with containerisation using Docker and containers management. Strong software engineering skillset including code review: a good understanding of coding best practices and experience with code and More ❯