- Over 12 years of extensive experience in AI/ML, with a proven track record of architecting and delivering enterprise-scale machine learning solutions across the Retail and FMCG domains.

- Demonstrated ability to align AI strategy with business outcomes in areas such as customer experience, dynamic pricing, demand forecasting, assortment planning, and inventory optimization.

- Deep expertise in Large Language Models (LLMs) and Generative AI, including OpenAIs GPT family, ChatGPT, and emerging models like DeepSeek.

- Adept at designing domain-specific use cases such as intelligent product search, contextual recommendation engines, conversational commerce assistants, and automated customer engagement using Retrieval-Augmented Generation (RAG) pipelines.

Technical Skills :

- Strong hands-on experience developing and deploying advanced ML models using modern data science stacks including :

1. Python (advanced programming with focus on clean, scalable codebases).

2. TensorFlow and Scikit-learn (for deep learning and classical ML models).

3. NumPy, Pandas (for data wrangling, transformation, and statistical analysis).

4. SQL (for structured data querying, feature engineering, and pipeline optimization).

- Expert-level understanding of Deep Learning architectures (CNNs, RNNs, Transformers, BERT/GPT), and Natural Language Processing (NLP) techniques such as entity recognition, text summarization, semantic search, and topic modeling with practical application in retail-focused scenarios like product catalog enrichment, personalized marketing, and voice/text-based customer interactions.

- Strong data engineering proficiency, with experience designing robust data pipelines, building scalable ETL workflows, and integrating structured and unstructured data from ERP, CRM, POS, and social media platforms.

- Proven ability to operationalize ML workflows through automated retraining, version control, and model monitoring.

- Significant experience deploying AI/ML solutions at scale on cloud platforms such as AWS (SageMaker, Bedrock), Google Cloud Platform (Vertex AI), and Azure Machine Learning.

- Skilled in designing cloud-native architectures for low-latency inference, high-volume batch scoring, and streaming analytics.

- Familiar with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML (MLOps).

Leadership & Communication :

- Ability to lead cross-functional teams, translating technical concepts into business impact, and collaborating with marketing, supply chain, merchandising, and IT stakeholders.

- Comfortable engaging with executive leadership to influence digital and AI strategies at an enterprise level.