Purpose/Objective

The Gen AI Data Scientist is responsible for the execution, optimization, and deployment of Generative AI models, ensuring high-performance AI solutions that enhance business efficiency, decision-making, and automation. This role involves hands-on model development, fine-tuning LLMs, and collaborating with cross-functional teams to integrate AI into enterprise applications.

Key Responsibilities of Role

Gen AI Data Scientist-AI Labs AI Model Development & Deployment: Develop, fine-tune, and deploy Generative AI models, leveraging transformer architectures, LLMs, and retrieval-augmented generation (RAG) frameworks. Optimize model accuracy, efficiency, and scalability by conducting rigorous training, testing, and hyperparameter tuning. Leverage AI frameworks and tools (LangChain, OpenAI, Azure OpenAI, Hugging Face, TensorFlow, PyTorch) to streamline AI deployment and monitoring. Ensure seamless AI model integration with enterprise workflows, APIs, and automation tools to improve business efficiency. Business Problem Solving with AI: Apply Generative AI, NLP, and deep learning to extract valuable insights from unstructured data and solve complex business problems. Develop AI-powered decision-support systems that enhance predictive analytics, risk assessment, and process automation. Ensure AI adoption and business value realization by aligning AI solutions with enterprise strategy, productivity, and automation goals. AI Research, Experimentation & Continuous Improvement: Enhance AI model performance by experimenting with data augmentation, prompt engineering, and model fine-tuning. Evaluate and integrate emerging AI techniques to improve model generalization, interpretability, and robustness. Stay updated on Generative AI advancements, publishing research insights, case studies, and technical documentation for internal teams.



Cross-Functional Collaboration & AI Implementation: Collaborate with business leaders, data engineers, and IT teams to ensure AI models are aligned with enterprise goals. Work closely with the model deployment team to ensure smooth transition of AI models from development to production. Engage with front-end development teams to enable seamless user experiences for AI-driven applications. Compliance, Governance & AI Ethics: Ensure AI models are compliant with data privacy laws (GDPR, AI Act) and organizational AI governance standards. Proactively monitor AI model drift, hallucinations, and interpretability issues, ensuring consistent AI performance and reliability. Mitigate AI bias and risks, promoting fair, ethical, and transparent AI decision-making. Key Stakeholders - Internal AI & Data Science Teams Business Leaders & Strategy Teams IT & Cloud Engineering Teams Compliance & Legal Teams Key Stakeholders - External Technology Partners & AI Vendors Research & Academia Regulatory Bodies

Technical Competencies

AI Governance, Compliance & Ethical AI-SDIL,AI Model Development & Optimization-SDIL,AI Product & Solution Development-SDIL,AI Research, Experimentation & Emerging Technologies-SDIL,AI Strategy & Enterprise Transformation-SDIL,Computer Vision & Image Processing-SDIL,Cross-Functional Collaboration & AI Integration-SDIL,Python Programming & AI Development-SDIL

Qualifications and Experience

Educational Qualification: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. Certification: Certified AI Engineer (Microsoft, AWS, Google AI Certification). Deep Learning Specialization (Coursera Stanford). NLP & LLM Certification (Hugging Face, OpenAI). Work Experience (Range of years): 3-5 years of hands-on experience in data science, specializing in Generative AI, LLMs, NLP, and Text Analytics.

📌 Gen AI Data Scientist-AI Labs (Gujarat)
🏢 Adani Group
📍 Gujarat