Software Developer Machine Learning Prompt tuning AWS

Apurva Sriram

**************@*****.*** +1-929-***-**** *******@***.***

EDUCATION EXPERIENCE

New York University PAYPAL SOFTWARE ENGINEER (FTE) Jul ‘21 – Jun ‘ 22 MS IN COMPUTER SCIENCE

May 2024 NY, USA

Cum. GPA: 3.9/ 4.0

NIT TRICHY

B. TECH (HONs.) IN ECE

MINOR - COMPUTER SCIENCE

May 2021 INDIA

Cum. GPA: 9.13/ 10

LINKS

LinkedIn: apurvasriram

Github: Apurvasriram

Portfolio: apurvasriram

COURSEWORK

Data Structures and Algorithms

Database Management System

Software Engineering

Optimization Techniques

Artificial Intelligence

Machine Learning

Computer Vision

Big Data

Cloud Computing

Networks and Protocols

Internet, Security and Privacy

Financial Information Systems

Natural Language Processing

PROJECTS

Restaurant Concierge Chat Bot

Smart Photo-Album System

Image Search Engine

Food Recipe Website

Song Playlist Recommender System

Customer Segmentation Analysis

Sarcasm Detection in Social Media

Fraud Detection System

Churn Prediction System

Cryptogram Puzzle Solver

Email Verifier Tool With Go

SKILLS

• Python • C \ C++ • Java • R • ReactJs

• SQL • AWS • Git • Docker

• Kubernetes • Jenkins • Terraform

• MongoDB • TensorFlow • PyTorch

• Spark • HTML • CSS • JavaScript

• Flask • Linux • GCP • GO

• Developed Recommender app using Python and Tableau with an accuracy of 97% to optimize redirects in customer complaint calls

• Conducted data-driven research and analysis, leading to a 20% reduction in build time and 15% increase in stability for the Jenkins pipeline, exhibiting expertise in data-informed decision-making, process optimization, and continuous integration/deployment practices

• Developed a template in Terraform for regression pipeline to be created as part of any new component created in the future

NYU COURSE ASSISTANT Sep ‘23 – May ‘24

• Spearheaded teaching initiatives for 500+ students in a Python course, creating 20+ instructional slides and 20 interactive lab notebooks, resulting in 85% pass rate and top ratings for the quality of course materials, showcasing expertise in Python, instructional design, and communication.

VOLT AI DATA SCIENCE INTERN May ‘23 - Aug ‘23

• Enhanced LLM model precision by 20% through implementation of a Python- based web scraping tool, designed to gather Q&A format data for model training.

• Developed and deployed a highlighting feature to provide insights into sources of response from the LLM model, boosting customer satisfaction by 15% SAMSUNG SOFTWARE ENGINEER INTERN May ‘20 – Jun ‘20

• Implemented customized Contiguous Memory Allocator with DMA-BUF API buffer Sharing mechanism for multimedia applications using C and Linux

• Devised kernel modules for importer and exporter enabling user-space buffer access sans memory location knowledge.

MICROSOFT (ALLY.IO) SOFTWARE ENGINEER INTERN Dec ‘19 – Jan ‘20

• Increased subscription management by 10% by modifying the admin dashboard using Ruby on Rails framework.

• Demonstrated proficiency in the Software Development Life cycle (SDLC) by participating in every stage, including creating JIRA stories, coding, testing, and deploying changes into live production.

OTHER PROJECTS

DOCONNECT - AI-POWERED MEDICAL CONSULTATION PLATFORM

• Engineered a symptom-based disease prediction chatbot, leveraging a Random Forest model trained and deployed using SageMaker. This formed a key component of a full-stack web application for doctors, which also included a networking platform for knowledge sharing and event updates, as well as a patient data record system utilizing Elasticsearch, DynamoDB, Lambda, Amazon S3 PREDICTIVE ANALYTICS FOR NYC PARKING

• Analyzed 15M+ parking records, finding top violations, and developing a Random Forest model for predicting next expected time and type of violation. This strategic intervention will optimize staff management and boost efficiency by 5%. OPTIMIZING ONLINE SPORTS RETAIL REVENUE

• Optimized online sports retailer’s revenue by 12% through exploratory analysis of multi-table dataset records on product, pricing, and customer data. Utilized advanced SQL techniques such as aggregations, correlations to identify key customer segments and tailor pricing strategies ACHIEVEMENTS

• Grace Hopper Celebration '23 Scholar

• Represented Government of India (GOI) at Youth Summit

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