Responsibilities :

- Provide data science and AI expertise to design, build, and deliver scalable ML and deep learning solutions.

- Work extensively with tabular data to develop predictive models, perform feature engineering, and optimize performance for real-world applications.

- Apply conventional machine learning techniques (e.g., regression, classification, ensemble methods) alongside advanced deep learning methods.

- Build and optimize deep learning models for structured and unstructured data, including text and audio.

- Lead development of solutions for audio data, including classification, recognition, and signal processing tasks.

- Design, fine-tune, and deploy LLMs (Large Language Models), SLMs (Small Language Models), and other Generative AI solutions for diverse business applications.

- Translate business problems into well-structured ML/AI problems and deliver actionable insights.

- Deploy production-grade models with a focus on efficiency, scalability, and maintainability.

- Collaborate with cross-functional teams including product managers, engineers, and domain experts to deliver high-impact projects.

- Mentor junior data scientists and interns, fostering innovation and best practices.

Qualification Requirements :

Educational :

- Bachelor's degree with at least 7 years of experience or Master's with at least 4 years of experience in Data Science/ML/AI.

- Preferred to have degree from a Tier-1/2 institute (IIT/IISc/NITs if studied in India) or a globally top-ranked university (as per QS).

Technical :

- Proven expertise working with large-scale tabular data and building machine learning models.

- Strong knowledge of conventional ML algorithms (tree-based models, SVMs, clustering, etc.).

- Hands-on experience with deep learning frameworks such as TensorFlow / PyTorch.

- Mandatory expertise in LLMs, SLMs, and Generative AI, including fine-tuning, prompt engineering, and deployment.

- Proficiency in Python and libraries such as scikit-learn, pandas, NumPy.

- Exposure to model deployment frameworks and tools (ONNX, Triton, TensorRT, FastAPI, etc.).

- Familiarity with cloud platforms (Azure/GCP) for training and deploying ML solutions.

- Experience with Databricks is a plus.

- Strong understanding of MLOps practices, reproducibility, and model monitoring.

Other :

- Excellent written and verbal communication skills in English.

- Demonstrated experience working collaboratively in cross-functional teams.

- Ability to balance research and production priorities while meeting deadlines.

- Passionate about applying AI/ML to solve diverse real-world problems, especially at the intersection of GenAI and enterprise AI adoption.