Ai Ml Engineer

Role & responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions to solve complex business problems.
• Build, train, evaluate, and optimize Machine Learning and Deep Learning models for production use cases.
• Develop Computer Vision applications including image classification, object detection, segmentation, and OCR solutions.
• Design and implement Natural Language Processing (NLP) solutions for text classification, information extraction, sentiment analysis, summarization, and conversational AI.
• Build forecasting and predictive analytics models using statistical and machine learning techniques.
• Develop and deploy Generative AI applications using Large Language Models (LLMs) for enterprise use cases.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines to enable accurate and context-aware AI responses.
• Develop AI agents and multi-agent workflows using Agentic AI frameworks.
• Build LLM-powered applications using LangChain, Hugging Face Transformers, vector databases, and embedding models.
• Fine-tune open-source and foundation LLMs using parameter-efficient techniques such as LoRA, QLoRA, and supervised fine-tuning (SFT).
• Implement prompt engineering, prompt optimization, and evaluation frameworks to improve LLM performance.
• Integrate AI solutions with REST APIs, enterprise applications, and third-party services.
• Deploy, monitor, and scale AI/ML models on AWS and GCP using cloud-native services and MLOps best practices.
• Build scalable ML pipelines for data preprocessing, model training, inference, and continuous deployment.
• Optimize model performance, inference latency, and infrastructure costs for production environments.
• Collaborate with data engineers, software developers, product managers, and business stakeholders to deliver AI-driven solutions.
• Ensure model governance, security, responsible AI practices, and compliance with organizational standards.
• Stay current with advancements in Machine Learning, Generative AI, LLMs, and emerging AI technologies, and recommend innovative solutions.

Preferred candidate profile

Should be strong with Core AIML things like Machine learning, Computer vision, Deep learning, NLP & Forecasting (Good to have)

Agentic & Gen AI-LLM, RAG, Langchain, Fine tuning of LLMs, Hugging face.

Cloud Deployments using AWS/GCP.