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Open to roles · US · MMXXVI
Issue No.02 · Timeline · Work and education

A record of
how I got here.

Path so far: graduate school, machine-learning roles, backend systems, and the work that shaped how I build.

2016 - presentSix entriesWork, study, and milestones.
Experience
4+ years
Backend, ML, and full-stack delivery
Education
2 degrees
Mumbai to Buffalo
Current base
Buffalo, NY
Open to remote and onsite roles
Chronology
2025
Work
Jan 2025 - Dec 2025

Software Engineer Intern

Filmic Technologies
RecentBuffalo, NY

Leading full-stack development for a digital media platform spanning marketplace flows, admin tooling, and blockchain-backed payments.

  • •Built the MVP from scratch with React, Next.js, and Nest.js on AWS EC2, S3, and CloudFront.
  • •Shipped uploads, real-time chat, RBAC, and admin operations for three user types in roughly three months.
  • •Set priorities, delegated work, and mentored interns while keeping delivery on schedule.
Tools / focus
Next.jsNest.jsAWSCloudFrontWebSockets
2024
Education
Aug 2024 - Dec 2025

M.S. in Computer Science & Engineering

University at Buffalo, SUNY
GraduatedBuffalo, NY

Graduate study focused on systems, machine learning, and production-oriented software engineering.

Tools / focus
AlgorithmsMachine LearningDeep LearningSystems
2023
Work
Aug 2023 - Aug 2024

Founding ML Engineer

Learno.AI
PreviousRemote

Owned AI and backend development for an ed-tech MVP that helped the founders reach a YC-ready product demo.

  • •Took the MVP from roadmap to working delivery in two months using Streamlit, FAISS, and LlamaIndex.
  • •Built a parser for visually complex PDFs by combining vision transformers with classical PDF extraction.
  • •Handled backend services, vector search, and CI/CD for the education chatbot platform.
Tools / focus
PythonFAISSLlamaIndexOpenSearchComputer Vision
2022
Work
Sep 2022 - Jul 2023

Software Engineer, Machine Learning

Signimus
PreviousRemote

Worked on computer vision systems, image-processing pipelines, and GPU-backed infrastructure for production workloads.

  • •Fine-tuned MODNet on private data and improved person-segmentation accuracy by 8.27%.
  • •Provisioned AWS compute, storage, CUDA dependencies, and monitoring for memory-intensive services.
  • •Implemented visual filters and GAN-based image workflows across the product stack.
Tools / focus
PythonMODNetOpenCVCUDAAWS
2021
Work
Sep 2021 - Aug 2022

Software Engineer, Machine Learning

Expertrons
PreviousRemote

Built recommendation and ML systems for a large user platform with measurable product and latency gains.

  • •Developed a mentor-matching recommender for roughly 250k active users.
  • •Cut short-video API processing time by 90% through MongoDB indexing and backend tuning.
  • •Worked with product and tech leadership on deep-learning features for user media enhancement.
Tools / focus
PythonMongoDBRecommendation SystemsImage Segmentation
2016
Education
Aug 2016 - Nov 2020

B.Tech. in Information Technology

University of Mumbai · Vidyalankar Institute of Technology
GraduatedMumbai, India

Built the technical foundation in software engineering, data structures, and applied computing before moving into ML-heavy roles.

Tools / focus
Data StructuresOperating SystemsResearchSoftware Engineering