Principal Data Scientist

Scope of the Role:

The Principal Data Scientist will lead the architecture, development, and deployment of cutting-edge AI solutions, driving innovation in machine learning, deep learning, and generative AI. The role demands cutting edge expertise in advanced Gen AI development, Agentic AI development, optimization, and integration with enterprise-scale applications while fostering an experimental and forward-thinking environment.

This senior level hands-on role offers an immediate opportunity to lead next-gen AI innovation, drive strategic AI initiatives, and shape the future of AI adoption at scale in large enterprise and industry applications.

Reports To:

Reportees:

Minimum Qualification:

Bachelor’s or Master’s/PhD in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or a related field. Advanced certifications in AI/ML frameworks, GenAI, Agentic AI, cloud AI platforms, or AI ethics preferred.

Experience:

• A minimum of 15+ years of experience in AI/ML, with a proven track record in deploying AI-driven solutions – and deep expertise and specialty in Generative AI (use of proprietary and open source LLMs/ SLMs/ VLMs/ LCMs, experience in RAG, fine tuning and developing derived domain-specific models, multi agent frameworks and agentic architecture, LLMOps)
• Expertise in implementing the Data Solutions using Python programming, pandas, numpy, sklearn, pytorch, tensorflow, Data Visualizations, Machine Learning Algorithms, Deep Learning architectures, LLMs, SLM, VLM, LCM, generative AI, agents, prompt engineering, NLP, Transformer Architectures, GPTs, Computer Vision, and ML Ops for both unstructured and structured data, synthetic data generation

• Experience in building generic and customized Conversational AI Assistants

• Experience working in innovation-driven, research-intensive, or AI R&D-focused organizations.
• Experience in building AI solutions for Construction or Manufacturing, Oil & Gas industries would be good to have.

Objective / Purpose:

The Principal Data Scientist will drive breakthrough AI innovation for pan-L&T businesses, by developing the scalable, responsible, and production-ready Gen AI and Agentic AI models using RAG with multi LLMs and derived domain specific models where applicable. This role involves cutting-edge research, model deployment, AI infrastructure optimization, and AI strategy formulation to enhance business capabilities and user experiences.

Key Responsibilities:

• AI Model Development & Deployment: Design, train, and deploy ML/DL models for predictive analytics, NLP, computer vision, generative AI and AI Agents.
• Applied AI Research & Innovation: Explore emerging AI technologies such as LLMs, RAG (Retrieval-Augmented Generation), fine tuning techniques, multi-modal AI, agentic architectures, reinforcement learning, and self-supervised learning with application-orientation.
• Model Optimization & Scalability: Optimize AI models for inference efficiency, explainability, and responsible AI compliance.
• AI Product Integration: Work collaboratively with business teams, data engineers, ML Ops teams, and software developers to integrate AI models into applications, APIs, and cloud platforms.
• AI Governance & Ethics: Ensure compliance with AI fairness, bias mitigation, and regulatory frameworks (GDPR, CCPA, AI Act).
• Cross-functional Collaboration: Partner with business teams, UX researchers, and domain experts to align AI solutions with real-world applications.
• AI Infrastructure & Automation: Develop automated pipelines, Agentic model monitoring, and CI/CD for AI Solutions

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Technical Expertise:

• Machine Learning & Deep Learning: TensorFlow, PyTorch, Scikit-learn, Regression, Classification, clustering, Ensembling techniques – bagging, boosting, recommender systems, Probability distributions and data visualizations
• Generative AI & LLMs: OpenAI GPT, Google Gemini, Llama, Hugging Face Transformers, RAG, CAG, KAG, knowledge on Other LLMs, SLM, VLM, LCM, Langchain
• NLP & Speech AI: BERT, T5, Whisper
• Computer Vision: YOLO, OpenCV, CLIP, Convolutional Neural Networks(CNN).
• ML Ops & AI Infrastructure: ML flow, Kubeflow, Azure ML.
• Data Platforms : Databricks, Pinecone, FAISS, Elasticsearch, Semantic Search, Milvus, Weaviate
• Cloud AI Services: Azure Open AI & Cognitive Services.
• Explainability & Responsible AI: SHAP, LIME, FairML.
• Prompt Engineering
• Publish internal/external research papers, contribute to AI patents, and present at industry conferences and workshops.
• Evaluate Open-Source AI/ML frameworks and commercial AI products to enhance the organization’s AI capabilities.

Behavioural Attributes:

• Business Acumen – Ability to align AI solutions with business goals.
• Market Foresight – Identifying AI trends and emerging technologies.
• Change Management – Driving AI adoption in dynamic environments.
• Customer Centricity – Designing AI solutions with user impact in mind.
• Collaborative Leadership – Working cross-functionally with diverse teams.
• Ability to Drive Innovation & Continuous Improvement – Research-driven AI development.

Key Value Drivers:

• Advancing AI-driven business transformation – securely, optimally and at scale
• Reducing time-to-value for AI-powered innovations.
• Enabling AI governance, compliance, and ethical AI adoption.

Future Career Path

The future career path will be establishing oneself as a world class SME having deep domain experience and thought leadership around application of next gen AI technologies in the construction, energy and manufacturing domains. Career would progress from technology specialization into leadership roles, in various challenging positions such as Head – AI Strategy and Chief AI Officer, in driving the enterprise AI strategies, governance, and innovation for various ICs/BUs across the pan L&T Businesses.