Senior Data Scientist, Generative AI & LLM Engineering

What you'll do

• Perform advanced exploratory data analysis and statistical analysis to identify actionable business insights.
• Design, develop, evaluate, and deploy machine learning models for predictive analytics and enterprise use cases.
• Build Generative AI and LLM-based solutions including RAG applications, AI agents, and enterprise search.
• Fine-tune, benchmark, and optimize LLMs for quality, latency, accuracy, scalability, and cost efficiency.
• Design model evaluation frameworks covering performance, relevance, hallucination, safety, and robustness.
• Develop and operationalize MLOps/LLMOps pipelines for model experimentation, versioning, deployment, and monitoring.
• Contribute to end-to-end AI/ML architecture across cloud and on-premises environments.
• Ensure AI solutions follow enterprise security, data governance, and responsible AI standards.

What we're looking for

• 6+ years of experience in Data Science, Machine Learning, AI Engineering, or Advanced Analytics roles.
• 3+ years of hands-on experience developing and deploying production-grade machine learning models.
• Expert knowledge of Exploratory Data Analysis, statistical methods, feature engineering, and machine learning algorithms.
• Hands-on experience with Generative AI and LLMs, including RAG, prompt engineering, embeddings, and vector databases.
• Proficiency in Python and ML/AI frameworks such as Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
• Experience with LLM fine-tuning, model benchmarking, inference optimization, and responsible AI practices.
• Familiarity with AI agents, multi-agent systems, MLOps/LLMOps, and enterprise AI platform architecture.
• Experience with major cloud AI/ML platforms such as Azure, AWS, or GCP.