Senior Data Scientist - Generative AI/NLP

Job Description :

We are looking for a Senior Data Scientist with strong hands-on experience in machine learning, GenAI, NLP, and LLM-based solutions. The role will involve developing, deploying, and scaling production-grade AI solutions using Python, cloud platforms, and MLOps practices.

Key Responsibilities :

• Design, develop, and deploy scalable machine learning and GenAI solutions for business use cases.

• Develop predictive and statistical models using Python, with strong focus on model performance, scalability, and production readiness.

• Work on NLP, LLM, and Generative AI use cases including text processing, embeddings, semantic search, and intelligent applications.

• Develop solutions using LLM APIs and open-source LLMs, including prompt engineering and model integration.

• Work with NLP and transformer-based models such as BERT and other relevant architectures.

• Perform exploratory data analysis, feature engineering, model development, validation, and performance optimization.

• Build and expose AI/ML solutions through APIs and production services.

• Implement ML deployment, monitoring, versioning, and automation using MLOps practices.

• Work with cloud platforms, preferably Microsoft Azure, to build and deploy scalable AI/ML solutions.

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

• Stay current with developments in GenAI, LLMs, NLP, ML frameworks, and AI engineering practices.

Required Skills :

• 8 - 13 years of experience in Data Science / Machine Learning / AI, with strong hands-on development experience.

• Strong proficiency in Python and machine learning libraries/frameworks.

• Strong experience in Machine Learning, GenAI, LLMs, and NLP.

• Hands-on experience with LLM APIs, open-source LLMs, embeddings, and transformer-based models such as BERT.

• Experience with PyTorch and/or TensorFlow.

• Strong understanding of model development, validation, EDA, feature engineering, and statistical techniques.

• Experience deploying ML/AI models and applications in production.

• Good understanding of MLOps, model monitoring, versioning, and CI/CD.

• Experience with at least one major cloud platform; Azure preferred.

• Strong understanding of REST APIs and production-grade AI/ML services.

• Strong problem-solving, communication, and stakeholder management skills.