Artificial Intelligence and Machine Learning Engineer with AWS Cloud Expertise

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Infosys in Bengaluru is seeking an AI/ML Engineer with hands-on AI/ML development experience and strong Python skills to drive end-to-end model projects. You will develop, train, evaluate, and deploy models for real-world business use cases on AWS.

Responsibilities include building GenAI/LLM solutions, RAG pipelines, integrating AWS Bedrock/OpenAI APIs, and implementing MLOps, monitoring, and containerized deployment with Docker.

Qualifications

• 2–3 years hands-on AI/ML development experience.
• Strong Python programming skills.
• Experience deploying ML models on AWS.
• Understanding ML lifecycle from data prep to deployment.
• Exposure to SageMaker and AWS cloud services.
• GenAI/LLM projects experience preferred.
• Exposure to LangChain, RAG and vector databases.
• Knowledge of MLOps and model monitoring.
• Familiar with Docker and containerized deployments.
• AWS Cloud or AWS ML certification a plus.

Responsibilities

• Develop, train, evaluate, and deploy ML models for business use cases.
• Build predictive analytics, classification, regression, recommendation, and NLP solutions.
• Work with structured and unstructured datasets for model development.
• Perform feature engineering, model tuning, and performance optimization.
• Develop applications using LLMs and Generative AI technologies.
• Build Retrieval-Augmented Generation (RAG) pipelines.
• Integrate foundation models through AWS Bedrock or OpenAI APIs.
• Implement prompt engineering and LLM evaluation techniques.

Skills

Python programming

ML lifecycle

MLOps

Feature engineering

Model evaluation

Tools

AWS SageMaker

AWS Bedrock

LangChain

Vector Databases

Docker

OpenAI APIs

LLMs

Job description

• AI/ML Engineer (with AWS Cloud Skills) 2-3 years of hands-on AI/ML development experience
• Strong Python programming skills
• Experience developing and deploying ML models on AWS
• Understanding of ML lifecycle from data preparation to deployment
• Exposure to SageMaker and AWS cloud services
• Experience with GenAI/LLM projects is highly preferred
• Experience with AWS Bedrock and Foundation Models.
• Exposure to LangChain, RAG, and Vector Databases.
• Knowledge of MLOps practices and model monitoring.
• Familiarity with Docker and containerized deployments.
• Certification in AWS Cloud or AWS Machine Learning is a plus.
• Develop, train, evaluate, and deploy Machine Learning models for business use cases.
• Build predictive analytics, classification, regression, recommendation, and NLP solutions.
• Work with structured and unstructured datasets for model development.
• Perform feature engineering, model tuning, and performance optimization.
• Develop applications using LLMs and Generative AI technologies.
• Build Retrieval-Augmented Generation (RAG) pipelines.
• Integrate foundation models through AWS Bedrock or OpenAI APIs.
• Implement prompt engineering and LLM evaluation techniques.