Description

Key Skills: Machine Learning, Pyspark, AI/ML, Cloud, DevOps, AWS

Roles and Responsibilities:

• Lead and mentor MLOps and AI/ML engineers; define engineering standards for ML system design, deployment, and operations.
• Develop and optimize supervised, unsupervised, and deep learning workflows using PySpark, MLlib, and PyTorch.
• Design and deploy ML solutions on AWS using EKS, EC2, SageMaker, Lambda, and S3 for orchestration and runtime execution.
• Automate cloud provisioning and configuration using Terraform and Infrastructure as Code (IaC) best practices.
• Build model-serving APIs with FastAPI and implement CI/CD pipelines for ML models using GitHub Actions or Jenkins.

Skills Required:

• 8 - 12 years of experience in ML engineering, MLOps, or related roles.
• Machine Learning, AI/ML, and DevOps practices for production ML systems.
• PySpark and MLlib for scalable data processing and model development.
• AWS services including EKS, EC2, SageMaker, Lambda, and S3 for deployment and orchestration.
• FastAPI-based APIs and CI/CD pipelines using GitHub Actions or Jenkins; Terraform and Infrastructure as Code (IaC).

Good to Have:

• AWS experience (additional depth across services and deployment patterns).

Education: Relevant degree in Computer Science, Engineering, or related field

Key Skills

Education

Any Graduate