Senior Data Scientist (Gen AI)
IDFC FIRST Bank · Bengaluru
- Experience2–6 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelmid
- Posted2 Sept 2026
About IDFC FIRST Bank
IDFC FIRST Bank is hiring in Bengaluru in financial services. This role looks for around 2+ years of experience.
Skills
- Generative AI
- large language models
- Python
- R
- Hugging Face Transformers
- TensorFlow
- PyTorch
- machine learning pipelines
- prompt engineering
- SQL
- NoSQL
- Natural Language Processing
- text analytics
- semantic search
- predictive modeling
- tokenization
- lemmatization
The role
A generative AI engineer at a banking and financial services company designs and deploys large language models for conversational agents, content generation, and semantic search, using Natural Language Processing and machine learning pipelines. The role also develops AI-powered APIs and services and applies text analytics to unstructured datasets.
Full job description
Responsibilities:
Lead cross-functional teams in the design, development, and deployment of generative AI solutions, with a strong focus on large language models (LLMs).
Architect, train, and fine-tune state-of-the-art LLMs (e. g., GPT, BERT, and T5) for various business applications, ensuring alignment with project goals.
Deploy and scale LLM-based solutions, integrating them seamlessly into production environments and optimizing for performance and efficiency.
Develop and maintain machine learning workflows and pipelines for training, evaluating, and deploying generative AI models, using Python or R and leveraging libraries like Hugging Face Transformers, TensorFlow, and PyTorch.
Collaborate with product, data, and engineering teams to define and refine use cases for LLM applications such as conversational agents, content generation, and semantic search.
Design and implement fine-tuning strategies to adapt pre-trained models to domain-specific tasks, ensuring high relevance and accuracy.
Evaluate and optimize LLM performance, including handling challenges such as prompt engineering, inference time, and model bias.
Manage and process large, unstructured datasets using SQL and NoSQL databases, ensuring smooth integration with AI models.
Build and deploy AI-driven APIs and services, providing scalable access to LLM-based solutions.
Use data visualization tools (e. g., Matplotlib, Seaborn, Tableau) to communicate AI model performance, insights, and results to non-technical stakeholders.
Secondary Responsibilities:
Contribute to data analysis projects, with a strong emphasis on text analytics, natural language understanding, and generative AI applications.
Build, validate, and deploy predictive models specifically tailored to text data, including models for text generation, classification, and entity recognition.
Handle large, unstructured text datasets, performing essential preprocessing and data cleaning steps, such as tokenization, lemmatization, and noise removal, for machine learning and NLP tasks.
Work with cutting-edge text data processing techniques, ensuring high-quality input for training and fine-tuning large language models (LLMs).
Collaborate with cross-functional teams to develop and deploy scalable AI-powered solutions that process and analyze textual data at scale.