Description

You will architect and lead end-to-end data and AI platforms, covering data ingestion, processing, and model training.

Responsibilities

• Design and deploy production-grade AI/ML solutions on AWS using S3, EC2, EKS/ECS, Lambda, RDS, and IAM.
• Build scalable batch and real-time pipelines for data engineering, ML, and generative AI workloads.
• Implement Retrieval-Augmented Generation (RAG) architectures, integrating LLMs with structured and unstructured data.
• Manage ML Ops and LLM Ops practices, including model/version management, prompt management, evaluation, and monitoring.
• Develop large-scale, complex datasets, handling transformation, normalization, and data quality management.

Required Skills

• 10+ years of professional experience in data engineering or ML engineering.
• Expert proficiency in Python.
• Deep experience with AWS services (S3, EC2, EKS/ECS, Lambda, RDS, IAM).
• Hands-on experience with ML frameworks like PyTorch and Scikit-learn.
• Proven ability to operate ML workloads in AWS GovCloud, adhering to security and compliance.
• Experience designing and implementing RAG architectures.
• Solid understanding of supervised and unsupervised learning techniques (classification, clustering).
• Familiarity with data security, privacy, and compliance in regulated environments.

Key Skills

Education

Any Gradute