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, predictivemodelling, and data-driven automation, closely collaborating with data engineering and product teams.

Responsibilities

• 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.

Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related fields.
• 23 years of hands-on experience in Machine Learning / AI projects.
• Hands-on experience building Generative AI applications using Large Language Models (LLMs) .
• Experience with prompt engineering, retrieval-augmented generation (RAG), and integrating LLMs with structured and unstructured data sources.
• Experience leveraging enterprise GenAI platforms and frameworks (e.g., Snowflake Cortex, Databricks Mosaic AI, OpenAI-compatible APIs) to build scalable AI solutions.
• Strong programming skills in Python and ML libraries like XGBoost, Pytorch, Tensorflow.
• Strong understanding of Model Evaluation Techniques and Feature Engineering.
• Proficientwith SQL and data handling.
• Strong experience with model deployment.
• Experience applying MLOps practices, including CI/CD for ML workflows and 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