Role Overview :

We are seeking an experienced and highly skilled Sr. Data Scientist to join our dynamic team. In this role, you will play a critical role in developing, training, fine-tuning LLM Models. The role is an intersection of AIML, Generative AI and Technology. You will be required to develop key integrations with RAG, develop modules and solutions for Agentic AI Platform as well as train/fine-tune models on proprietary data. While the role would be a combination of AI and Tech - it is highly weighed toward AI. You will be involved in developing innovative solutions to complex business problems. You will collaborate closely with cross-functional teams to extract actionable insights from large and diverse datasets, enabling the company to make informed strategic decisions.

- Develop and implement advanced statistical, ML/AI, and LLM models to solve complex business problems and optimize performance.

- Fine-tune and train domain-specific LLMs, including multi-modal (text, speech, vision, image) models.

- Hands-on experience with fine-tuning LLMs using LoRA, PEFT, or similar methods.

- Design and implement RAG systems and GenAI architectures (e.g., Knowledge Graphs, modular agent architectures) for enhanced agent outcomes.

- Translate GenAI problems into AI/ML problem statements and design optimal solution architectures.

- Read, interpret, and implement complex academic research, adapting it into scalable, enterprise-ready AI systems.

- Collaborate with academic and research partners to co-develop innovative solutions, publish findings, and integrate cutting-edge methods.

- Lead end-to-end data science pipelines : data collection, cleaning, feature engineering, model development, validation, deployment.

- Explore and analyze large datasets to derive insights and inform business strategies.

- Build cost-optimized, scalable AI solutions across multi-cloud environments.

- Apply MLOps/LLMOps practices for model lifecycle management and continuous improvement.

- Collaborate with cross-functional stakeholders to align AI solutions with business objectives.

- Mentor and guide junior data scientists, contributing to team growth and capability building.

Required Qualifications :

- Master's or Ph.D. degree in a quantitative field such as Computer Science, Statistics, Mathematics, or related discipline. (Candidates with exceptional industry experience may be considered without advanced degrees.

- Proven track record in data science, with hands-on experience in developing and deploying statistical and machine learning models in a production environment.

- Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).

- Strong knowledge and experience in a wide range of statistical modeling techniques (e.g., regression, clustering, time series analysis, Bayesian inference, NLP, LLM Fine-Tuning) and machine learning algorithms (e.g., decision trees, random forests, neural networks).

- Strong knowledge and experience in training Image Models, Speech Model, Text Models - using Transformers, Pre-Trained Models, Model Fine-Tuning techniques

- Solid understanding of database systems and proficiency in SQL for data retrieval and manipulation.

- Excellent problem-solving skills and the ability to work with large and complex datasets, identifying relevant variables, and developing meaningful insights.

- Strong communication and interpersonal skills, with the ability to effectively present complex findings to both technical and non-technical audiences.

- Proven ability to work in a collaborative and fast-paced environment, managing multiple projects and priorities simultaneously.

Important Soft Skills :

- Builder Mindset : Passion for creating systems that work end-to-end. Comfortable starting from ambiguous requirements and iterating rapidly.

- Customer Orientation : Ability to translate business needs into practical solutions that deliver measurable value for clients.

- Startup Agility : Thrives in fast-paced environments. Able to self-manage, prioritize, and drive initiatives independently.

- AI-Native Curiosity : Openness to leveraging AI tools, agents, and emerging automation techniques to improve productivity and design smarter systems.