Suryansh S.

Software Engineer

Bengaluru, Karnataka, India4 yrs 6 mos experience

Key Highlights

Optimized banking notification services, improving throughput by 30%.
Engineered a recurring payments service ensuring compliance with security standards.
Developed a CRF sequence tagger, enhancing NLP classification accuracy.

Stackforce AI infers this person is a Fintech and EdTech software engineer with strong expertise in backend systems and machine learning.

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Skills

Core Skills

Spring BootGoKafkaMonitoringMvc ArchitectureMachine Learning

Other Skills

API-first architectureAerospikeApache KafkaBatch processingBlockchainCRFCaching mechanismsConcurrent ProgrammingData AnalysisDatabase indexingDistributed CachingDistributed SystemsEncryptionEthereumFastText

About

Hello World!

Experience

Paytm payments bank

Software Engineer

Oct 2021 – Dec 2022 · 1 yr 2 mos

Software Engineer – Bank Authentication & Payments Platform
Optimized a centralized notification service (push, SMS, email) serving as the core communication hub for multiple banking services; implemented Kafka-backed queueing and batch processing pipelines, improving throughput by 30% and integrating Aerospike-backed caching for templates/user preferences, reducing DB query load by 20% and cutting response latency.
Engineered a new recurring payments & mandate management service from the ground up using Spring Boot & Go, enabling customers to view, manage, and revoke standing instructions (e.g., Netflix, Spotify) directly within the Paytm app; ensured compliance with RBI e-mandate guidelines and PCI-DSS security standards.
Integrated observability stack – configured New Relic, Grafana, and Kibana to monitor distributed microservices; defined custom KPIs & alerting rules, enabling proactive issue detection and real-time incident response.
Delivered API-first architecture: Authored comprehensive OpenAPI/Swagger specifications, onboarding docs, and operational runbooks to streamline cross-team integration and reduce onboarding time for new engineers.

KafkaSpring BootGoAPI-first architectureNew RelicGrafana+2

Icici lombard

2 roles

Software Engineer

Jul 2020 – Sep 2021 · 1 yr 2 mos

SDE Intern

Jan 2020 – Jul 2020 · 6 mos

Redesigned the Payment Processing System, transitioning from WebForms to MVC architecture, resulting in a more lightweight application
Achieved significant improvements in page load times and server performance, reducing load time by 35% and enhancing server response rate by 50%
Optimized backend processes by implementing caching mechanisms, database indexing, and connection pooling, leading to a 25% increase in overall system efficiency
Collaborated with cross-functional teams to ensure seamless integration of the redesigned system with existing infrastructure, minimizing downtime and ensuring smooth user experience
Employed best practices in code management, utilizing Git for version control and continuous integration for streamlined deployment
Conducted thorough testing and debugging to maintain the highest standards of security, stability, and reliability in the updated Payment Processing System

MVC architectureCaching mechanismsDatabase indexingGit

Iiit hyderabad

Research Intern

May 2019 – Jan 2020 · 8 mos · Hyderabad, Telangana, India · Hybrid

💡 Turning Lecture Chaos into Structured Conversations
My first hands-on dive into NLP and Machine Learning, where I built systems to make lecture transcripts context-aware and machine-understandable.
Key Contributions
Developed a Conditional Random Field (CRF) sequence tagger to classify lecture utterances as monologue or dialogue using sentence-level tagging.
Enhanced performance by experimenting with TF-IDF features, FastText embeddings, and Dialogue Act tags to capture speaker intent.
Worked on Anaphora Resolution to help models correctly interpret references like “he” or “him” in academic transcripts.
Collected and annotated diverse lecture data from Stanford, Harvard CS50, and NPTEL to train and evaluate the models.
Improved classification accuracy from 59.5% to 64.1% through iterative experimentation and feature engineering.
Tech Stack: Python, FastText, Stanford CoreNLP, Scikit-learn, CRF++

PythonCRFFastTextStanford CoreNLPScikit-learnMachine Learning

Project vision

Co-Founder and Technical Project Lead

May 2018 – Jul 2020 · 2 yrs 2 mos · Manipal · On-site

Manipal's first student project racing towards
developing technologies that are designed to solve
critical outstanding technological problems in virtual and mixed reality systems. Our vision is to stand the test of time as we continue to build technology solutions that will enhance and enrich
the quality of life within and around us.