Job Description
About the Role
We're seeking Big & Deep Learners to join our pioneering team developing Paytm Large Model (PLM), a foundation model for digital payment intelligence.
You'll be at the forefront of :
Building and tweaking big transformer architectures on big data of payment and other activities (onboarding, login, order, invest, )
Build Encoder to create embeddings that capture the DNA of payment ecosystems
Further build Decoder or Autoregressive Generative model for behavioural prediction/detectionDo whatever it takes to enrich and use the model for downstream applications : IFT/DPO/RPO.
Key Responsibilities-
Design and develop large-scale foundation models for learning from payment transactions, user behavior, merchant patterns etc
- Create sophisticated encoder architecture to generate embeddings that capture nuanced relationships in financial data
- Build decoder only model as well for generative downstream tasks
- Build and optimize training pipelines for processing billions of payment transactions
- Develop evaluation frameworks for measuring model performance across multiple financial use cases
- Implement fine
- tuning mechanisms for model adaptation across different payment environments
- Collaborate with MLOps team for production deployment and scaling
- Research and implement latest advances in foundation models and their applications to financial data
- Make the model wiser everyday by enriching it through state of the art IFT, DPO, PPO .
Required Qualifications-
Preferred Experience-
- Previous work with financial or transaction data
- Experience with large encoder/decoder models and representation learning
- Knowledge of privacy
- preserving ML techniques
- Background in self
- supervised learning approaches
- Familiarity with MLOps and production deployment of large models
- Experience with model compression and optimization techniques
- Working knowledge on Knowledge Graph representation learning using Graph Neural Network (GraphSage/GAT/Graph Transformer ..) is a plus
Technical Skills-
Languages: Python, PySpark, SQL- Frameworks: PyTorch/TensorFlow, Hugging Face- Infrastructure: Cloud platforms (AWS/GCP), distributed training systems- Tools: Git, Docker, ML experiment tracking platforms- Processing: Spark, distributed computing
Soft Skills-
Strong research orientation with practical implementation skills- Ability to translate complex technical concepts to business stakeholders- Excellence in technical writing and documentation- Collaborative mindset for cross-functional team projects
Job Classification
Industry: Banking
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Scientist
Employement Type: Full time
Contact Details:
Company: Paytm
Location(s): Bengaluru
Keyskills:
data scientist
time series analysis
technical writing
python
batch processing
sql
docker
compensation and benefits
deep learning
tensorflow
git
data science
spark
gcp
use cases
pytorch
onboarding
aws
architecture