Job Description

Job Description: GenAI / Data Science EngineerRole OverviewWe are looking for a GenAI / Data Science Engineer with 3–8 years of hands-on experience in building and deploying AI solutions.The role focuses on enterprise-grade Generative AI and Data Science use cases with strong emphasis on Python, LLMs, and production deployment.Key ResponsibilitiesDesign, develop, and deliver Generative AI solutions for enterprise use cases.Build and optimize LLM-based solutions including RAG pipelines and model fine-tuning.Develop NLP pipelines for text processing, embeddings, and semantic search.Train, evaluate, and deploy ML/AI models into production environments.Implement MLOps practices for model versioning, monitoring, and lifecycle management.Collaborate with engineering, data, and business teams to translate requirements into scalable AI solutions.Work with cloud platforms (AWS, Azure, or GCP) for model deployment and data processing.Mandatory Skills (Must-Have)3–8 years of experience in GenAI and/or Data Science roles.Strong proficiency in Python for data science and ML development.Hands-on experience with Large Language Models (LLMs), including RAG architectures and/or fine-tuning.Solid understanding of NLP techniques and text-based ML models.Experience deploying ML models using MLOps practices (CI/CD for ML, monitoring, retraining).Experience working on at least one major cloud platform: AWS, Azure, or GCP.Proven delivery of enterprise-grade AI/ML solutions.Good-to-Have SkillsExperience with vector databases and embedding-based retrieval.Familiarity with frameworks such as LangChain, HuggingFace, or similar.Exposure to data engineering tools and pipelines.Experience working in regulated or large enterprise environments.