Description

You will design and build large-scale AI and ML infrastructure.

Responsibilities

• Design enterprise architectures on AWS, Google Cloud, or Azure.
• Create scalable architectures for Machine Learning Operations and AI workloads.
• Implement cloud storage, blob storage, indexing services, and vector databases.
• Develop data pipelines, ETL processes, and data lakes for ML systems.
• Establish model evaluation and monitoring systems to address model drift and inaccuracy.

Required Skills

• 5+ years of experience in enterprise architecture.
• Proficiency with AWS, Google Cloud, and Azure environments.
• Hands-on experience with TensorFlow, PyTorch, Langchain, Huggingface, and OpenAI.
• Experience developing ETL Processes.
• Knowledge of Transformers, Transfer Learning, model tuning, and training.
• Experience implementing CI/CD for ML and AI containers.
• Understanding of cloud security principles, including zero-trust and least privilege.
• Ability to design cost-efficient systems for model training and validation.

Key Skills

Education

Any Graduate