AI/ML Engineer

We are looking for an AI/ML Engineer with a strong inclination toward Generative AI and Large Language Models (LLMs) to build intelligent, scalable, and production-grade AI applications. You will work on real-world use cases involving NLP, GenAI, predictive modelling , and data-driven automation, closely collaborating with data engineering and product teams.

• Design, develop, train, and deploy machine learning and Generative AI models for real-world business use cases including prediction, automation, NLP, and decision intelligence.


• Build and optimize LLM-powered applications such as chatbots, document intelligence systems, summarization engines, and RAG (Retrieval-Augmented Generation) pipelines with hands-on experience in LLMs, embeddings, vector search, and RAG architectures.


• Perform data preprocessing, feature engineering, model evaluation, and hyperparameter tuning to ensure accuracy, reliability, and scalability.


• Develop and manage end-to-end ML and GenAI pipelines, including training, validation, versioning, deployment, monitoring, and optimization.


• Work with Snowflake, Databricks and other cloud platforms (GCP, AWS, Azure) to enable scalable data-driven AI solutions.


• Monitor model performance, drift, cost, and latency, and apply continuous optimization to production AI systems.


• Collaborate with cross-functional teams to translate business problems into scalable AI solutions.


• Apply AI governance, security, and responsible AI practices across ML and LLM systems.

Experience:

• Bachelor s or Master s degree in Computer Science, Data Science, AI/ML, or related fields.


• 2 3 years of hands-on experience in Machine Learning / AI projects.


• Strong programming skills in Python and ML libraries like XGBoost, Pytorch, Tensorflow.


• Strong understanding of Model Evaluation Techniques and Feature Engineering.


• Experience with SQL and data handling.


• Strong experience with model deployment.


• Basic understanding of MLOps concepts (CI/CD for ML, model versioning).


• Hands-on experience with LangChain, LlamaIndex, and LangGraph to orchestrate agents, workflows, and multi-step AI pipelines.


• Working experience with platforms like Snowflake, Databricks is a plus