Ameya Ranade

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 core workflows and seeing those systems move from early design conversations into tools that people actually depend on every day has been the most satisfying part of the job.
  • A lot of my work at the end of last year went into building the admin and configuration layer — a suite of interfaces that let teams configure underwriting rules and system settings without touching code. Getting that right meant thinking carefully about caching and making the whole experience feel snappier. Similarly, I worked on asynchronous audit logging that offloads payload comparison to background services entirely, which kept our APIs fast and reduced the time it takes to review an audit by 65%.
  • The deeper insurance domain work has been some of the most interesting. Integrating Risk Analyst into Xponent's underwriting workflows meant touching 8,000+ submission data fields — enriching them, validating them, making sure the data coming in was actually good enough to inform a risk decision. Commercial and Specialty lines are unforgiving; bad input data leads to bad pricing, and bad pricing leads to real losses. Getting that integration right required understanding both the technical pipeline and why the data mattered in the first place.
  • I also own production reliability for Magic Submission, our AI-driven pipeline for ingesting submissions. If Magic Submission goes down, submissions pile up and brokers notice. Keeping it up has meant building good observability habits from the start: structured log monitoring across distributed services, fast root cause analysis, and learning how Grafana, Loki, and AWS services fit together to triage and debug under pressure.

    • 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 was mentored by Wenlong Zhao and we collaborated closely with Min Li and Saloni Potdar, whose guidance helped shape the project’s direction. 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

    M.S. in Computer Science

    University of Mumbai

    2019 — 2023

    B.Tech in Information Technology with a Minors in Management

    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)