Job Description

Job role: GenAI / Machine Learning Engineer - Payments (Chennai)

Job Type:

Fulltime

Job Mode:

Onsite/Chennai

Experience:

8yrs-10yrs

Gen AI engineers (Python / LangGraph mandatory)

Expertise in Python and LangGraph for building Generative AI products.

Mandatory Skills:

Deep learning (CNN , RNN ,GAN , Transformers , Encoder and decoder architecture), Generative AI , Python

NLP, Generative AI , Chatbot, any cloud knowledge like Azure

We are seeking an experienced Machine Learning Engineer with strong expertise in Generative AI (GenAI) and payment data analytics to join our team. In this role, you'll work on large-scale credit card and UPI transaction data to identify use cases, develop PoCs, and build production-ready ML and GenAI solutions that unlock insights and drive innovation in payments.

Key Responsibilities:

Data Handling & Feature Engineering:
Collect, preprocess, and analyze payment datasets (credit card, UPI) to extract meaningful features, including embeddings, time-series signals, and customer behavior patterns.

ML Model Development:
Design and implement models for fraud detection, customer segmentation, and demand forecasting using tools like TensorFlow, PyTorch, and Scikit-learn.

Generative AI & Foundation Models:
Apply and fine-tune OSS LLMs (e.g., Hugging Face Transformers, Llama, GPT-J, Falcon) for use cases such as:

Synthetic data generation Transaction summarization Conversational AI for payment-related queries Model Evaluation & Optimization:
Use metrics like AUC-ROC, precision, recall, and F1-score to evaluate models. Apply hyperparameter tuning and distributed training for performance improvement.

Deployment & MLOps:
Deploy ML/GenAI models using tools like MLflow, Kubeflow, SageMaker, and Docker/Kubernetes. Set up real-time inference pipelines and monitor model drift and reliability in production.

Collaboration & Communication:
Work with cross-functional teams (data scientists, engineers, product) to define requirements and deliver business-impacting solutions. Present findings to both technical and non-technical stakeholders.

Requirements:

Bachelor's or master's degree in computer science, engineering, mathematics, statistics, or a related field. 8-10 years of proven experience as a

Machine Learning Engineer

,

Data Scientist

, or similar role. Strong knowledge of

machine learning

,

statistics

, and

data science concepts

and techniques. Proficient in programming languages such as

Python

,

R

, and Java*.
Experience with data processing tools like

SQL

,

Spark

, and

Hadoop

. Proficient in using frameworks like

TensorFlow

,

PyTorch

,

Scikit-learn

,

Hugging Face Transformers

, and other OSS LLMs. Hands-on experience with foundational models, such as

BERT

,

GPT

,

T5

, and

Vision Transformers (ViT)

. Experience with

credit card

and

UPI payment data

use cases (e.g., fraud detection, transaction risk assessment, customer analytics) is a plus. Experience fine-tuning and deploying OSS LLMs for specific tasks such as

text summarization

,

synthetic data generation

, and

NLP applications

in payments. Familiarity with frameworks/tools like

Hugging Face

,

LangChain

, and

LlamaIndex

. Hands-on experience deploying ML and GenAI models in production environments with tools like

MLflow

,

Kubeflow

,

Docker

, and

Kubernetes

. Excellent communication and presentation skills, with the ability to explain complex concepts
Job Types: Full-time, Permanent

Pay: ?1,500,000.00 - ?2,200,000.00 per year

Work Location: In person