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.