Description

Design and deploy machine learning models and infrastructure within cloud environments.

Build and maintain ML operations and engineering workflows.

Develop REST APIs to serve machine learning models.

Manage infrastructure components using containerization and CI/CD pipelines.

Collaborate with cross-functional teams to solve complex technical issues.

Apply software engineering best practices including version control, code review, and testing.

Required Skills

• 5+ years of hands-on experience in ML operations or ML engineering.
• Experience with AWS SageMaker.
• Proficiency with AWS or Azure cloud platforms.
• Experience with REST API development and AWS Networking Protocols.
• Hands-on experience with Docker.
• Hands-on experience with CI/CD pipelines.
• Bachelor's degree in Computer Science, Data Science, or a related field.

Preferred Skills

• Familiarity with load balancing, EKS (Kubernetes), and ML model serving techniques like NVIDIA Triton.
• Experience with the Hugging Face Diffusers Library.

Key Skills

Education

Any graduate