Description

Design and architect scalable platforms for machine learning workloads across on-prem and cloud environments.

This role is on-site.

Responsibilities

• Design AI/ML platform architectures supporting the full model development lifecycle.
• Implement software and data engineering principles to support machine learning workflows.
• Deploy and manage containerized workloads using orchestration tools.
• Integrate CI/CD pipelines into the ML development process.

Required Skills

• 5+ years of experience in AI/ML platform architecture.
• Deep understanding of ML algorithms and deep learning architecture.
• Hands-on experience with TensorFlow, PyTorch, and Scikit-Learn.
• Expertise in GCP or Azure and their specific AI services.
• Proficiency with containerization and orchestration tools.
• Strong grasp of software engineering and data engineering principles.
• Experience managing the model development lifecycle.
• Knowledge of CI/CD implementation.

Preferred Skills

• Experience with hybrid cloud deployments.
• Familiarity with MLOps best practices.

Key Skills

Education

Any Graduate