We are seeking an experienced Data Scientist with expertise in Machine Learning, Python, NLP, LLMs, MLOps, and cloud infrastructure automation.

The ideal candidate will design, develop, and deploy high-performance ML models and build scalable AI-driven applications.

Key Responsibilities :

- Build & Deploy ML Models : Develop machine learning models for NLP, Computer Vision, or predictive analytics and deploy them using FastAPI or Flask.

- Data Architecting : Design and manage SQL/NoSQL databases, integrating Vector Databases for AI-driven retrieval and scalable solutions.

- Code Excellence : Write production-ready Python code, implement automated ETL pipelines, and follow best practices for maintainable, scalable software.

- Scaling & Optimization : Optimize model inference and database queries to ensure high-performance applications.

- Collaborate with cross-functional teams to implement ML solutions in production environments.

- Ensure reproducibility, version control, and monitoring of ML pipelines.

- Apply MLOps practices for model deployment, monitoring, and maintenance on cloud infrastructure.

Must-Have Skills :

- Strong expertise in Machine Learning (ML) and Deep Learning.

- Proficient in Python for production-grade ML and data engineering workflows.

- Hands-on experience with NLP and Large Language Models (LLMs).

- Familiarity with MLOps, model deployment, monitoring, and CI/CD for ML pipelines.

- Experience with cloud infrastructure automation (AWS, Azure, or GCP).

- Knowledge of SQL and NoSQL databases, with experience integrating Vector Databases for AI retrieval.

- Ability to write clean, maintainable, and scalable code for production systems.

Good-to-Have :

- Experience with computer vision projects.

- Exposure to automated ML pipelines and containerization (Docker/Kubernetes).

- Familiarity with high-performance computing and model optimization techniques