1 to 5 of 5 Amazon SageMaker Jobs in England with Remote Work Options

team, and the BBC will provide many opportunities for learning as you progress. We create and support reliable and scalable cloud-based services on Amazon Web Services, use GitHub for version control and practice pair programming and Test-Driven Development where possible. Here is the list: • Experience of modern … Python development software engineering best practices • Knowledge of software development principles, design patterns and best practices • Experience with AWS services such as SageMaker, S3, EC2, VPC, Lambda, Redshift • Experience with relational and non-relational databases, data modelling and design principles. • Test Driven Development and testing practices. • Knowledge of infrastructure more »

leading a data science team and managing complex projects. Expertise in machine learning, statistics, data management, and relevant technologies (e.g., Python, R, SQL, AWS SageMaker, Apache Airflow, Dbt, AWS Kinesis). Strong communication skills with the ability to explain complex data concepts to a non-technical audience. Knowledge of more »

engineering practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries more »

models to build a better future where a new job is just a click away. Your responsibilities: Implement and productionise ML-based services using Sagemaker Collaborate with Data Scientists to design and implement LLM-based inference workflows Utilize IaC and CI/CD best practices to increase efficiency in … years of experience in Machine Learning Engineering, Data Engineering, or a related field Proficiency in production-level Python (Clean, SOLID) and industry experience with Amazon Sagemaker deployment of LLMs Experience with LLM-related packages, such as PyTorch, Transformers etc. Experience with IaC (Terraform), CI/CD, and test more »

for everybody. Your responsibilities: Work together with the AI labs, Data, Infrastructure, and Platform teams to design and deploy ML-based services using AWS Sagemaker and other cloud based solutions. Analyse current AWS account setup for data scientists & MLEs and improve it together with StSt MLE & DevOps experts. Understand … Labs teams to advance current ML workflows and software development standards. Qualifications Your skills and qualifications Industry experience in AWS ML services, including AWS Sagemaker Experience in DevOps, Cloud Operations, ML-engineering, AWS administration and permission management. Expertise with building enterprise scale ML & LLM solutions, Docker, IaC (Terraform), CI more »