L&T Financial Services - Senior AI Scientist (5-15 yrs)

About Company : L&T Finance

L&T Finance is a leading non-banking financial company (NBFC) in India, part of the larger Larsen & Toubro (L&T) Group.

Established in 1994, L&T Finance has grown into a diversified financial services provider, offering a wide range of products including retail and corporate finance, housing finance, asset management, and wealth management services.

With a strong focus on technology and innovation, L&T Finance is committed to leveraging cutting-edge solutions to enhance its financial products and services, improve customer experiences, and drive sustainable growth in the rapidly evolving Indian financial sector.

About Team :

We are a high performance advanced predictive and generative AI team, operating out of Bangalore and Mumbai.

The team is comprised of intelligent and enthusiastic data scientists and ML engineers with a proven track record. We are focused on bringing cutting edge AI technologies to sharpen and grow the lending businesses of L&T Finance.

Role Overview :

We are seeking experienced Senior AI Scientists to join our team.

- The ideal candidate will have a strong background in Machine Learning and/or Generative AI, with proficiency across both areas.

- This role offers the flexibility to specialize in one area while contributing to projects across both domains.

Experience :

We welcome applications from candidates with a range of experience levels : Typically, we look for 5-15 years of experience in Machine Learning and/or Generative AI.

- However, we recognize that expertise doesn't always correlate directly with years of experience.

Exceptional candidates with less than 5 years or more than 15 years of experience are encouraged to apply if they can demonstrate strong capabilities in AI and ML.

- We value skills, knowledge, and the ability to innovate over strict experience requirements.

Qualification

- BS/BTech from Tier 1 institution, or MS/MTech from Tier 1 institution

Location

- Mumbai or Bangalore

Key Responsibilities

1.

Design and develop end-to-end machine learning models and GenAI workflows on GCP Vertex AI and other platforms.

Fetch and process data from BigQuery and various sources for model development.

Build and deploy models using Python and frameworks such as Scikitlearn, XGBoost/CatBoost, TensorFlow, Keras, and Gemini.

Implement and work with a wide range of ML algorithms, including Regression, Classification, Forecasting, Unsupervised Learning, and Natural Language Processing.

Develop and deploy computer vision solutions, including preprocessing of image and video data.

Utilize and fine-tune state-of-the-art language models (LLMs) and foundation models for specific tasks and applications.

Implement advanced AI technologies like Retrieval-Augmented Generation (RAG) and function calling to enhance LLM capabilities.

Build and maintain ML models in production for both real-time and batchbased use cases.

Conduct exploratory data analysis and feature mining across structured and unstructured data sources.

- Develop and implement evaluation metrics to measure ML and LLM model performance and effectiveness.

- Apply CI/CD & MLOps best practices for model deployment and automation of ML pipelines & monitoring.

- Stay up-to-date with the latest advancements in machine learning, GenAI, and related AI/ML technologies.

Required Skills and Experience :

- Strong proficiency in Python

- Expertise in Data Science and Machine Learning

- Experience with Natural Language Processing and Deep Learning

- Familiarity with Docker and Flask

- Proficiency in TensorFlow and Keras

- Experience with GCP Vertex AI, Vertex Pipelines, MLOps, Cloud Functions, BigQuery, Cloud Run, AutoML, DocAI, Gemini, Cloud Build, Artifact Registry, and Vertex AI endpoints

Desired Experience

- Experience in the Banking Financial Service Industries (BFSI) and/or B2C applications

- Knowledge of model and data explainability, bias mitigation, and best practices in highly regulated industries

- Hands-on experience with hyperparameter tuning and related best practices/tools

- Experience with reinforcement learning, with or without human feedback, for continuous model fine-tuning

- Familiarity with LLM frameworks like Langchain and LlamaIndex

- Experience with computer vision libraries such as OpenCV

Additional Qualifications (Good to Have)

- GCP - Google Certified Professional Machine Learning Engineer certification

- Advanced Certificate in Generative AI

- Strong background in statistics and probability

- Machine Learning / Data Science certifications or advanced coursework

- Knowledge of the BFSI and NBFC ecosystem

Key Technologies and Platforms

- Python, Scikit-learn, XGBoost/CatBoost, Pandas, NumPy

- TensorFlow, Keras, PyTorch

- Natural Language Processing (NLP) libraries

- Computer Vision libraries (e.

, OpenCV)

- GCP Vertex AI suite (including Gemini)

- BigQuery, Cloud Functions, Cloud Run

- Docker, Flask

- Langchain, LlamaIndex (for LLM applications)

The ideal candidate will have a strong foundation in either Machine Learning or Generative AI, with the ability to contribute across both domains.

We welcome applicants who excel in one area and are eager to expand their skills in the other, fostering a collaborative environment that bridges traditional ML and cutting-edge GenAI technologies

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