1 to 6 of 6 Amazon SageMaker Jobs with Hybrid or WFH Options

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 »

UML, Draw.io, and the Joint Enterprise Modeling and Analytics (JEMA) framework or Apache NiFi. Experience in AWS services including but not limited to EC2, Sagemaker, S3, EMR, and IAM. Our salary ranges are market-driven and set to allow for flexibility. Individual pay will be competitive based on a 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 »

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 »

Engineering Manager Type : Permanent Location : London Onsite Requirements : Hybrid - 2/3 days a week Salary : Ranging between £110,000 - £150,000 A leading global SaaS business at the forefront of cutting-edge technology are seeking a talented Engineer Manager more »