Hi, I'm Naman Lalit
Master's Student in Computer Science @ NYU Courant
Software Engineer Co-op @ Skillz
Former Software Engineer @ Salesforce
About
Driven by a passion for technology and problem-solving, I am a Computer Science graduate student at NYU Courant. With more than 2 years of professional experience in software development, I have honed my skills in languages and frameworks such as Python, Java, Golang, Node.js, React.js, C++, Javascript, Tensorflow, and Pytorch, as well as in cloud technologies like Docker, Kubernetes, CI/CD, AWS and Google Cloud.
I am seeking Full-Time Opportunities (Jun 2025) that challenge me to harness my technical expertise in software development and data science to make impactful contributions to the field.
Experience
- Building ACH Fast Withdrawal and Deposit features by integrating Aeropay payments using Golang backend and React Native SDK, driving an estimated $5M annual revenue increase.
- Developed a robust webhook framework in Golang, implementing 10+ event-handling scenarios (e.g., refunds, transaction failures, account suspensions), significantly improving transaction reliability.
- Delivered a key feature end-to-end for displaying targeted advertisements to players, using TypeScript and React Native, improving user conversion rates by approximately 60%.
- Pioneered the development of the Benefits Management Portal using the Salesforce Omnistudio tech stack, JavaScript, React.js, and Java, generating over $20 million in ACV.
- Collaborated with cross-functional teams and delivered a feature of automated PDF uploads on the Salesforce platform using Java, Spring, and Junit, increasing efficiency for over 100 developers.
- Led the Guided Setup project for 1 release, shipping multiple new features, fixing existing bugs, and collaborating with different teams for the successful delivery of the project.
- Integrated Einstein GPT bot as a service fine-tuned on the Public Sector Cloud, increasing customer productivity by 90%.
- Spearheaded feature discussions, successfully shipped multiple key features, authored comprehensive documentation, and ensured quality with rigorous unit and functional testing.
- Skills: Java, Spring, Salesforce Omnistudio, LWC, Experience Cloud, Junit, REST, Perforce.
- Led the back-end development of Report's product, used across the organization by more than 80+ members.
- Developed multiple features and integrated AWS services, including SQS, SES, DynamoDB, and S3 into the existing products using Node.js, and Rest APIs.
- Engineered and launched interactive dashboards using HTML, CSS, Node.js, React.js, Flask, Python, and MySQL, significantly boosting revenue by 50%.
- Automated the processing of over 5000 daily AWS SQS events using a Python script, efficiently storing data in a MongoDB database.
- Mentored 2 interns during their onboarding, and conducted knowledge transfer sessions, and developed comprehensive documentation for existing products.
- Skills: Node.js, Flask, Python, React.js, AWS (S3, SQS, SES, DynamoDB), HTML, CSS, Docker
- Reduced Redis memory usage by 50% by designing a Python script to delete unused game tickets.
- Streamlined and managed the migration of REST APIs from one service to another while overseeing the entire end-to-end deployment process using Java/Spring.
- Skills: Java, Spring, MySQL, Junit, AWS, Redis.
- Designed REST APIs using Flask and Python, wrote complex SQL queries on Google Big Query, and optimized query response time, reducing it from 200 ms to 20 ms by implementing Celery for efficient management of asynchronous tasks.
- Led the integration for Android and Backend Application with proper testing, and also performed load testing using Jmeter.
- Skills: Python, Flask, MySQL, Jmeter, Google Big Query, Ngrok.
Research
- Working with Prof. Anasse Bari and building an ensemble Retrieval Augmented Generation framework on LENR (Low Nuclear Energy), leveraging over 3000 pre-processed articles and integrating outputs from four LLMs (ChatGPT, Gemini, Claude, Llama 3).
- Led NYU's AI and Predictive Analytics team on the Politics Project, utilizing NLP and predictive analytics to forecast the 2024 presidential election, featured on CNN News.
- Worked with Prof. Justin Cappos and developed the core functionalities of an operating system (RustPosix) in Rust and C++, maintaining 100% code coverage and improving system reliability and performance.
- Built CI/CD pipelines using GitHub Actions and Docker, reducing deployment time by 80% and increasing development efficiency.
- Skills: Rust, C++, Github, CI / CD, Docker, Operating System
Education
NEW YORK, USA
Degree: Master of Science in Computer Science
GPA: 3.95/4.0
- Predictive Analytics
- Multicore Processor and Architecture
- Operating Systems
- Cloud Computing & Machine Learning
- Deep Learning
- Algorithms and Programming Languages
Relevant Courseworks:
NATIONAL INSTITUTE OF TECHNOLOGY HAMIRPUR
Himachal Pradesh, India
Degree: Bachelor of Engineering in Computer Science
GPA: 4.0/4.0
- Data Structures and Algorithms
- Database Management Systems
- Object-Oriented Programming
- Machine Learning
- Artificial Intelligence
Relevant Courseworks:
Projects
Stock Price Prediction tool built using LSTM and Large Language Model
Retrieval Augmented Generation (RAG) - Stock Research Recommendation System
NLP based Research Clustering and Document Analysis
CNN Model Optimization and Performance Analysis on Nvidia GPUs (A-100, V-100)
Skills
Languages
Python
C++
C
Java
Golang
Rust
Databases
MySQL
PostgreSQL
MongoDB
AWS DynamoDB
Google Big Query
Frameworks
HTML
CSS
Salesforce
Spring
Flask
Node.js
Angular
React
LangChain
Tools
Git
Github
Redis
Junit
Selenium Webdriver
Prompt Engineering
Kubernetes
Docker
CUDA
Cloud Services
Amazon Web Services
Google Cloud
Machine Learning
Deep Learning
Generative AI
Linear Regression
NLP
Sckit-learn
TensorFlow
PyTorch
Matplotlib