Description

You will design and deploy machine learning models and infrastructure within cloud environments.

Responsibilities

• 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