About this role
The team is seeking an experienced MLOps Engineer to join their dynamic team. The ideal candidate will have a strong background in machine learning operations, focusing on the deployment and management of machine learning models in cloud environments.
Key Responsibilities:
- Hands-on experience with AWS SageMaker, including training, deployment, and monitoring of machine learning models.
- Develop and maintain Python scripts using the SageMaker Python SDK.
- Work efficiently in Linux environments to support model lifecycle management.
- Utilize Docker to build and manage containerized SageMaker models.
- Implement and manage Terraform infrastructure for SageMaker and other AWS services.
- Collaborate with data scientists and engineers to streamline the ML workflow.
Required Skills & Qualifications:
- Proficiency in AWS services, particularly SageMaker.
- Strong programming skills in Python.
- Experience with Docker and containerization technologies.
- Familiarity with Terraform for infrastructure management.
- Solid understanding of machine learning concepts and model lifecycle management.
Experience:
- A minimum of 5-8 years of relevant experience in MLOps or related fields.
What we offer:
- Opportunity to work in a fast-paced and innovative environment.
- Professional development and career advancement opportunities.
- Collaborative team culture that values creativity and initiative.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.