2 jobs in National Payments Corporation Of India (NPCI)
Associate Fraud and Federated AI
Posted today
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Job Description
You will be part of NPCI’s Market Innovation team, working at the intersection of advanced machine learning, deep learning, graph AI, and Generative AI to build next-generation intelligent systems for India’s digital payments ecosystem.
This role focuses on solving India-scale problems such as fraud detection, mule/AML risk modeling, transaction intelligence, and conversational AI, using both classical ML and cutting-edge AI architectures (LLMs, GNNs, Transformers).
You will design end-to-end AI systems—from problem formulation, feature engineering, and model development to GPU-accelerated optimization and production deployment, ensuring low latency, scalability, and robustness.
The role offers a unique opportunity to work on:
Graph-based fraud detection systemsLLM-powered platforms (RAG workflows)GPU/CUDA optimized AI pipelinesPrivacy-preserving and federated AI systemsYou will collaborate with top academic institutions (IITs/IISc) and cross-functional teams to push the boundaries of applied AI in financial systems.
Job details Job Title: Data Scientist - Associate Fraud and Federated AIDivision: NPCI Market InnovationExperience: 1 to 3 YearsEducation: B.Tech / M.Tech / MSc / MCA (PhD preferred) in CS, AI, DS, Mathematics or related fieldEmployment Type: Full-timeLocation: Mumbai & HyderabadRole Type: PermanentKey responsibilitiesMachine Learning & Advanced Modeling
Develop and deploy ML/DL models (Logistic Regression, RF, XGBoost, NN, CNN, Transformers, GANs)Build models for fraud detection, AML, anomaly detection, transaction intelligenceWork on imbalanced datasets using advanced sampling and cost-sensitive learningGraph AI & Advanced Systems
Design Graph AI models: GNN, GCN, GAT, temporal graph networksApply network analytics for fraud rings, mule detection, behavioral risk signalsGenerative AI
Build LLM-powered applications (chatbots, complaint intelligence, document analysis)Implement: RAG pipelinesPrompt engineering & LLM fine-tuningFeature Engineering & Data Science
Perform EDA, feature engineering (temporal, behavioral, aggregated features)Work with structured, semi-structured, and unstructured dataModel Optimization & GPU Acceleration
Optimize models for: Latency & throughputGPU performance (CUDA-based optimization)Use libraries such as: RAPIDS, cuDF, cuML, cuGraph, PyTorch GeometricEvaluation & Experimentation
Design custom loss functions (weighted BCE, cost-sensitive)Apply business-aligned metrics: , Recall, ROC-AUC, PR-AUCUse robust validation techniques (cross-validation, time-based splits)Deployment & Production Systems
Integrate models into batch and real-time production systemsDesign scalable ML pipelines & APIsMonitor: Model driftPerformance stabilityBusiness impactCollaboration & Research
Work with data engineers, product teams, and business stakeholdersContribute to research, innovation, and academic collaborationsStay updated on latest AI advancements (LLMs, Graph AI, Federated Learning)RequirementsRequired Technical SkillsCore ML & Data Science
Strong in: Supervised & unsupervised learningStatistical modeling (Logistic Regression, DA)Tree models (RF, XGBoost, LightGBM)Deep Learning: NN, CNN, Transformers, GANsGenerative AI & LLM Stack
Hands-on experience with: LLMs (OpenAI, open-source models)Prompt engineering, fine-tuningRAG pipelines & vector databasesGraph AI
Experience with: GNN, GCN, GATGraph-based fraud detectionNetwork analyticsProgramming & Tools
Strong proficiency in: Python (NumPy, Pandas, scikit-learn)SQL (large-scale data processing)Frameworks: PyTorch / TensorFlowPyTorch GeometricGood to have skills and experience requiredExperience in:
Payments / fintech / banking domainFraud detection, AML, mule detection systemsExposure to:
Graph analytics on transactional dataFederated learning & privacy-preserving AIReal-time streaming systemsExperience with:
Cloud platforms (AWS/GCP/Azure)ML pipelines & MLOps frameworksResearch experience:
Publications in ML/AI conferences or journalsAbility to:
Design AI models inspired by mathematics/physics principlesIs this job a match or a miss?
Senior Associate Cloud Computing
Posted 20 days ago
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Job Description
NPCI is seeking an experienced DevOps Engineer with strong expertise in automation, Kubernetes, Linux systems, and networking. The candidate will design, build, and maintain scalable, secure, and highly resilient infrastructure powering NPCI’s critical digital payment platforms such as UPI, IMPS, RuPay, AePS, BBPS, NACH, and NETC Etc .
The role operates in a mission-critical, high-throughput, low-latency environment , ensuring 99.99%+ availability , transaction integrity, and system resilience aligned with RBI regulatory standards . The engineer will drive automation, improve observability, and enable reliable platform engineering at nation-scale transaction volumes .
Job Details Job Title: DevOps EngineerDivision: Cloud Computing & Data Center (DC) Years of Experience: 3–7 yearsEducation: Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).Certifications: CKA, CKAD, AWS/Azure/GCP DevOps certifications are a plus.Employment Type: Full-timeLocation: Hyderabad / ChennaiKey Responsibilities Design, implement, and manage CI/CD pipelines for secure and automated deployment across NPCI’s payment platforms (UPI, IMPS, RuPay, etc.).Deploy, manage, and optimize production-grade Kubernetes clusters supporting high TPS (transactions per second) workloads.Administer and troubleshoot Linux-based systems in high-availability Data Center environments.Configure and maintain networking for Kubernetes clusters (ingress, load balancing, DNS, service mesh – Istio, Linkerd ) ensuring ultra-low latency and fault tolerance.Build and enhance Internal Developer Platforms (IDPs) for self-service provisioning, improving developer velocity and governance.Automate infrastructure and operations using Terraform, Ansible, Helm, Pulumi across hybrid and private cloud ecosystems.Implement enterprise-grade monitoring, logging, and alerting systems (Prometheus, Grafana, ELK/EFK, Loki) for real-time observability and incident response.Containerize applications using Docker and orchestrate deployments on Kubernetes aligned with standardization practices.Ensure infrastructure security, compliance, auditing, and governance aligned with RBI guidelines, PCI-DSS standards, and NPCI policies .Collaborate with cross-functional teams (Engineering, SRE, Security, Network, Platform) to improve reliability, scalability, and developer productivity .Participate in incident management, root cause analysis (RCA), and system resilience improvements for mission-critical services.RequirementsKey Skills and Experience Required 3–7 years (up to 10 years flexible) of experience in DevOps, SRE, or Platform Engineering roles.Strong hands-on experience with Kubernetes (production-scale cluster operations and automation) .Deep expertise in Linux system administration (RHEL, Ubuntu, CentOS) in critical environments.Strong understanding of networking fundamentals (TCP/IP, DNS, routing, firewalls, VPN, load balancing) with exposure to high-performance systems.Experience with Infrastructure as Code (IaC) tools – Terraform, Ansible, Helm, Pulumi.Expertise in CI/CD tools – Jenkins, GitLab CI, GitHub Actions, ArgoCD, Flux.Experience with observability stacks – Prometheus, Grafana, ELK/EFK.Proficiency in scripting languages – Bash, Python, Go .Hands-on exposure to cloud and private cloud platforms (AWS, Azure, GCP, OpenStack).Understanding of distributed storage systems (Ceph, physical storage) and network stack (TCP/IP, Overlay Networking) .Experience working in high-availability / high-scale / transaction-heavy environments .Good to Have Skills and Experience Required Experience with service mesh architectures (Istio, Linkerd, Consul).Exposure to eBPF, CNI plugins, and advanced Kubernetes networking for performance tuning.Strong knowledge of security practices (RBAC, Pod Security Standards, Network Policies, Zero Trust principles).Familiarity with GitOps methodologies (ArgoCD, Flux) for continuous delivery.Experience working in regulated environments (RBI / BFSI / financial systems) .Is this job a match or a miss?