Description

Key Responsibilities

• Develop and optimize AI/ML solutions including LLMs, RAG, Agentic AI, and GenAI applications
• Implement and automate scalable ML pipelines using MLflow, AWS SageMaker, Databricks, and PySpark
• Establish CI/CD workflows, model versioning, monitoring, and automated retraining processes
• Leverage AWS AI/ML services (SageMaker, Bedrock, Lambda, Step Functions, ECS/EKS) for scalable solutions
• Optimize large-scale ETL workflows and distributed data processing with PySpark
• Fine-tune and deploy LLMs integrated with vector databases (FAISS, Pinecone, ChromaDB)
• Deploy and manage AI workloads using Kubernetes (EKS), Docker, and CI/CD pipelines

Qualifications

• 10+ years of experience in AI/ML engineering with strong Python coding skills
• Expertise in Machine Learning, Deep Learning, NLP, and Generative AI technologies
• Hands-on experience with LLMs, RAG architectures, and Agentic AI systems
• Proficiency in MLOps practices including model deployment, monitoring, and automated retraining
• Experience with AWS cloud services, containerization (Docker/Kubernetes), and CI/CD pipelines
• Bachelor's degree in Computer Science, Engineering, or related field

Key Skills

Education

Bachelor's degree