Mamaearth - AI Engineer - Machine Learning

We are looking for an experienced AI Engineer with 5-7 years of hands-on experience in developing, implementing, and deploying AI-driven solutions. The ideal candidate should have strong expertise in Python, machine learning, deep learning, NLP, Generative AI, and AI application development. The role involves working on end-to-end AI solutions, from understanding business requirements and preparing data to model development, evaluation, deployment, and optimization. Key Responsibilities Design, develop, and implement AI and machine learning solutions for business and product requirements. Develop and optimize machine learning and deep learning models. Work with structured and unstructured data for AI/ML applications. Develop AI-powered applications using Python and relevant ML/AI frameworks. Build and integrate Generative AI solutions, including LLM-based applications where applicable. Develop solutions using techniques such as NLP, text classification, information extraction, recommendation, and predictive modeling. Perform data preprocessing, feature engineering, model training, validation, and performance optimization. Evaluate models using appropriate performance metrics and continuously improve model accuracy and reliability. Develop APIs and services to integrate AI/ML models with enterprise applications. Collaborate with software engineers, data engineers, product teams, and business stakeholders. Deploy and monitor AI/ML models in development and production environments. Troubleshoot model, data, and application issues and implement appropriate solutions. Maintain technical documentation covering models, experiments, APIs, and deployment processes. Stay updated with emerging AI/ML technologies, frameworks, and industry practices. Required Technical Skills 5-7 years of experience in AI/ML or related software engineering roles. Strong programming experience in Python. Strong understanding of Machine Learning algorithms and concepts. Experience with supervised and unsupervised learning techniques. Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch. Good understanding of NLP and text-processing techniques. Experience with data preprocessing, feature engineering, model training, and evaluation. Experience working with ML libraries such as Scikit-learn, Pandas, and NumPy. Experience developing and integrating REST APIs for AI/ML solutions. Good understanding of software engineering principles and version control using Git. Generative AI - Good to Have Experience working with Large Language Models (LLMs). Understanding of Generative AI application development. Experience with prompt engineering and LLM integration. Knowledge of Retrieval-Augmented Generation (RAG) architectures. Exposure to vector databases and semantic search. Experience with frameworks such as LangChain or similar AI application frameworks. Understanding of model evaluation, monitoring, and responsible AI practices. Cloud & MLOps - Good to Have Exposure to AWS, Azure, or Google Cloud. Experience deploying models using cloud platforms. Understanding of Docker and containerization. Exposure to CI/CD and MLOps practices. Knowledge of model monitoring and production deployment. Key Competencies Strong analytical and problem-solving skills. Ability to translate business problems into practical AI solutions. Strong programming and debugging skills. Ability to work on end-to-end AI projects. Good communication and collaboration skills. Ability to work effectively with cross-functional teams - -