Ameya Ranade Resume

Experience

Software Engineer at Intellect Design Arena

July 2025 – Current NJ, USA

  • At IntellectAI, I work on Xponent, an underwriting workbench used by brokers and MGAs in commercial insurance. Most of my day is spent building the systems that automate the work underwriters used to do manually like compliance checks, risk scoring, premium calculations and much more. I’ve shipped several of the product’s core workflows and have gotten to see them move from whiteboard sketches to production tools that underwriters depend on.
  • Graduate Student Researcher at Apple

    Feb 2025 – June 2025 Remote

  • In collaboration with Apple, I explored a question that sounds simple but is deceptively tricky: when you read a long article, what are the few entities that actually matter? My work revolved around building few-shot systems that identify and disambiguate these “core” entities for Safari’s indexing pipeline.
  • I collaborated closely with Min Li and Saloni Potdar, whose guidance helped shape the project’s modeling direction. I was mentored by Wenlong Zhao. Wenlong fundamentally changed how I think about research: how to frame problems, cut through noise, and design experiments that actually reveal something. A lot of the system we built came from those conversations.
  • We’re now refining the ideas and preparing an updated version for ACL 2026 conference.
  • Founding Engineer at material.engineer (Stealth startup)

    June 2024 – Dec 2024 TX, USA

  • I joined as one of the earliest engineers at a small stealth startup building SpecGenie, an AI-powered automation platform to streamline EPC workflows. For EPC teams, manually generating and validating dozens of specification and catalog sheets is pure overhead: slow, error-prone, and painfully repetitive. Our product collapsed that entire design cycle from a week of back-and-forth work to under an hour of automated processing and human review, letting teams move faster from design freezing to fabrication and ultimately accelerating project schedules. I spent most of my time designing systems that made that possible.
  • I built 10+ end-to-end features and the core behind our pipeline that let EPC teams upload dense, unstructured piping specs and receive structured enterprise data back validated, cross-referenced, and ready for bulk ingestion!
  • We partnered with a Fortune 500 energy major, global energy companies in Abu Dhabi, and integrated with Hexagon, a key player in 3D plant design software. Working this closely with domain experts taught me just how much value emerges when you combine niche industrial data with well-designed AI systems.
  • ML Research Intern at Center for Machine Intelligence and Data Science (CMInDS)

    Jan 2022 – July 2022 Mumbai, India

  • At CMInDS, I worked on the very human problem of grading short answers. I built an Automatic Short Answer Grading system using stacked embeddings and ensemble models and pushed benchmark performance on the Mohler dataset by a meaningful margin. I implemented custom spell correction, experimented with cosine similarity variants, and trained per-question models that captured nuance better than a general-purpose model could.
  • Software Engineer Intern at LokaVidya Technologies

    July 2021 – Jan 2022 Mumbai, India

  • I helped build LokaVidya Meet, a video conferencing platform tailored for educational institutions. My work ranged from stitching together Node.js services with BigBlueButton APIs to implementing core meeting features like chat, moderation, and session control.
  • One of the more impactful projects was redesigning RBAC. The original version lived entirely in-memory, which meant access checks bogged down the database. Migrating to Redis turned it into a fast, cached system that sped up access decisions and relieved the backend significantly. It was my first real taste of how small architectural shifts create outsized performance wins.
  • Education

    University of Massachusetts Amherst

    2023 — 2025

    University of Mumbai

    2019 — 2023

    Teaching:

    • Grader for CS 532 (Systems for Data Science), Spring 2025
    • TA for CS 161 (Distributed Systems), Fall 2022

    Graduate-level technical coursework:

    • Algorithms for Data Science (CS 514)
    • Systems for Data Science (CS 532)
    • Applied Information Retrieval (CS 546)
    • Machine Learning (CS 589)
    • Robotics (CS 603)
    • Operating & Distributed Systems (CS 677)
    • Neural Networks (CS 682)
    • Advanced Natural Language Processing (CS 685)
    • Systems for Deep Learning (CS 690AB)
    • Independent Research (CS 696DS)

    Undergraduate technical coursework:

    • Probability and Statistics (MA203)
    • Discrete Structures and Graph Theory (IT201)
    • Data Structures (IT202)
    • Computer Architecture and Organization (IT203)
    • Database Management Systems (IT204)
    • Linear Algebra (MA201)
    • Design and Analysis of Algorithms (IT205)
    • Operating Systems (IT206)
    • Computer Communications and Networks (IT207)
    • Theory of Computation (IT301)
    • Software Engineering (IT302)
    • Distributed Computing (IT304)
    • Object Oriented Programming (IT305B)
    • Natural Language Processing (IT413)
    • Soft Computing (IT312)
    • Data Analytics (OEIT6)
    • Blockchain Technology (IT424)
    • Deep Learning (IT414)
    • Human Machine Interaction (IT413)
    • Advanced Database Systems (IT312)

    Leadership Roles:

    Chairperson of Computer Society of India, S.P.I.T chapter

    • Led a team of 20+, raising $6k+ for 9 tech events including the S.P.I.T Hackathon (150+ teams)

    Vice-Chairperson, Oculus

    • Managed 100+ members, raised $10k+, and coordinated operations for 5000+ attendees

    Awards and Honors

    Academic Achievements:

    • State Scholarship Examination: 9th in Maharashtra, 4th Grade (2011)
    • Pravinya Mathematics Examination: 1st in Maharashtra (2012)
    • Homi Bhabha Examination: Silver Medalist, 6th Grade (2013)
    • International Mathematics Olympiad (IMO): Gold Medalist, 9th Grade (2016)