Senior Data Scientist

About the Team

Mahindra AI Division is the AI innovation arm within Mahindra Group. The division experiments with state-of-the-art AI technologies and is focused on developing and delivering cutting-edge AI products to the group. With the division’s team-expansion plan, there is an excellent opportunity for your career growth in the team.

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.