We are looking for an experienced GenAI Data Scientist to design, develop, and deploy machine learning and Generative AI solutions across NLP and large-scale data environments. The role requires strong hands-on expertise in machine learning, NLP, LLMs, GenAI application development, and scalable data pipelines, with the ability to take models and AI solutions from experimentation through production.

Key Responsibilities :

- Design, develop, and deploy machine learning and Generative AI solutions for business and product use cases.

- Develop NLP and LLM-based solutions including text classification, information extraction, semantic search, summarization, question answering, and conversational AI.

- Work with LLMs, prompt engineering, embeddings, vector search, RAG, and LLM-based application architectures.

- Develop and evaluate AI solutions using appropriate model evaluation methodologies, datasets, and performance metrics.

- Build and optimize scalable data pipelines supporting ML model development, training, inference, and production workloads.

- Design pipelines with appropriate considerations for data volumes, SLAs, latency, freshness, backfill, data quality, and failure handling.

- Perform data preparation, feature engineering, experimentation, and statistical analysis to support machine learning solutions.

- Work with structured and unstructured data to develop high-quality datasets for ML and GenAI applications.

- Develop, test, and optimize machine learning models using appropriate frameworks and libraries.

- Collaborate with Data Engineers, Software Engineers, Product teams, and business stakeholders to translate requirements into production-ready AI solutions.

- Monitor model and pipeline performance and troubleshoot data, model, and production issues.

- Implement appropriate practices for model versioning, experimentation, reproducibility, and deployment.

- Stay current with developments in Generative AI, NLP, LLMs, machine learning frameworks, and AI engineering practices.

Requirements :

- 7 - 12 years of experience in Data Science, Machine Learning, NLP, or related fields, with hands-on experience in Generative AI/LLM solutions.

- Strong understanding of machine learning algorithms, statistical modelling, and data science methodologies.

- Strong hands-on experience in NLP and ML systems.

- Practical experience working with LLMs, Generative AI, prompt engineering, embeddings, RAG, vector databases, or related technologies.

- Strong programming skills in Python and experience with relevant ML/data science libraries and frameworks.

- Hands-on experience designing and delivering scalable data pipelines for ML or analytics workloads.

- Strong understanding of data processing, data quality, transformation, and pipeline reliability.

- Experience working with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, or equivalent.

- Experience with distributed data processing or data engineering technologies such as Spark, Databricks, Kafka, Airflow, or equivalent would be an advantage.

- Experience taking ML/GenAI solutions from experimentation/PoC to production.

- Strong analytical, problem-solving, communication, and cross-functional collaboration skills.