AI/ML Engineer

Responsibilities :

• Develop,Design, develop, and deploy scalable Machine Learning models for predictive analytics, classification, regression, recommendation, clustering, and forecasting problems.
• Build end-to-end AI pipelines covering data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop and fine-tune Large Language Models (LLMs) for enterprise use cases.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and embedding models.
• Build autonomous AI agents capable of planning, reasoning, memory management, and tool usage.
• Contribute to the establishment of best practices for efficient utilization of generative models in business and automation contexts.
• Work with leadership and stakeholders to identify AI opportunities and promote strategy.
• Be able to deliver solutions following modern software development practices.

Required Skills:

• Bachelor's degree in computer science, IT, AI or relevant discipline
• Must have minimum of 1 year of work experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps/LLMOps, Optimization techniques, and AI solutions.
• Specific experience in GenAI and Conversational AI – LLMs, frameworks like Lang chain, Llama Index etc, Vector DBs like Pinecone, Elasticsearch, etc.
• Solid proficiency in Python programming and related AI/ML libraries.
• Experience with cloud platforms (AWS, Azure, or GCP) for deploying and scaling AI/ML solutions.
• Experience with AI model evaluation, prompt optimization, and implementation of Responsible AI practice
• Knowledge of API integration, microservices architecture, and production-grade AI application deployment.
• Design GenAI application, integrating advanced models like OpenAI’s GPT, BERT or Open Source LLMs.
• Deep understanding of the RAG architecture and its implementation.
• Knowledge in SQL generation using LLM is preferred.
• Ability to write high-quality, maintainable code and work collaboratively.
• Knowledge of Agile software development lifecycle, including experience of applying change control procedures and disciplines required.
• Problem solving with strong analytical skills with the ability to analyse complex requirements and define technical / functional advanced solutions.
• Excellent communication skills in both verbal and written English