Akhilesh Chandra Machine learning engineer

I build the data and modelsthat physical AI runs on.

Machine learning engineer working on perception pipelines for robotics: segmentation, 3D mesh, pose and PII redaction across egocentric, stereo and fisheye video. Before that I built synthetic data pipelines for enterprise agents, shipped a voice assistant to npm, and spent three years finding critical vulnerabilities in software people use every day.

01

Experience

Jun 2026 onwardFellowship

Activate VC AI Fellow

  • Joined as an AI Fellow, learning and collaborating with other fellows on LLMs and AI agents.
Sep 2026Open source Contributions

Hebbian Robotics YC S26

  • Passed channel topics down to the MCAP reader, so selecting a channel by ID no longer decompresses every stream in the file. A small state channel sitting beside gigabyte-scale camera data now skips the unrelated chunks entirely, and channel ID filtering still holds when several channels share one topic.
  • Stopped SQL errors echoing the internal preview wrapper. A failed query was showing people a DESCRIBE SELECT * FROM (...) statement they never wrote. Execution-phase errors now drop that location block while keeping the diagnostic text, and parse errors keep theirs, because those do quote the caller's own SQL.
MCAPDuckDBPythonRobotics data
Aug 2026 to presentMachine learning

Fenon AI Machine Learning Engineer

  • Built the pipeline that generates segmentation, 3D mesh, masks, gloves and PII redaction for egocentric, stereo and fisheye video.
Segmentation3D meshPII redactionEgocentric video
Jul 2026 to Aug 2026Robotics

Peak AI Robotics Machine Learning Engineer

  • Built the pipeline for segmentation and PII redaction on egocentric, stereo and fisheye video.
  • Wired up GCP so videos could be sourced and a GPU job started in one click.
GCPGPU pipelinesComputer vision
Jun 2026 to Jul 2026Synthetic data

Deccan AI Machine Learning Engineer

  • Built an end to end ML pipeline for synthetic database generation across 10 tools, used to train enterprise agents.
  • Reached an 89% unique and related data fill rate across 60k rows.
  • Built both LLM and non-LLM approaches, plus a multi-commit diff approach for the Data forge pipeline.
  • Designed the architecture for the chain of thoughts project.
Synthetic dataLLM pipelinesAgents
Apr 2026 to Jun 2026Computer vision

Asai Labs Computer Vision Engineer

  • Created the architecture and defined every approach from scratch to build the shelf fill rate detection model for 180 stores of the biggest bakery in the CEE region.
Retail visionShelf analyticsModel architecture
Aug 2023 to presentSecurity

Independent Security Researcher

  • Found 8 critical vulnerabilities, including remote code execution, LFI and broken access control at Meta.
  • Reported a critical denial of service in Sequoia Open PGP, session hijacking in Firefox Nightly, and path traversal in Cash App and Expo Go.
  • Reported usability bugs at Booking.com and YouTube.
RCEAccess controlResponsible disclosure
Jan 2024 to Jan 2025Venture

GoAhead Ventures, Expert Dojo and LvlUp Ventures Venture Scout

  • Used my network to source early stage startups across AI, e-commerce and fintech.
  • Evaluated founding teams and product architecture for investment potential.
  • Built a working sense of what makes a startup scalable, what investors look for, and what users actually want.
Aug 2023 to Mar 2024Fintech

GoldNest Founder

  • GoldNest set out to make gold investing accessible to everyone: digital gold, physical gold, bonds and ETFs.
  • Built the prototype and presented it at IIT Roorkee and IIM Lucknow.
May 2022 to Aug 2023E-commerce

Axtra Co-Founder

  • An e-commerce startup focused on Gen Z fashion. In a team of 5 we built the app and brought brands on as vendors.
  • Led marketing that reached 11.1k+ people and 500+ followers in 3 days.
02

Projects

Physical AIDatasets and models

Dataset for Physical AI

Ready to train logs and usable models for physical AI in dark stores, factories and warehouses.

  • Human pose detection: identifies 17 human joints and the resulting pose in real time, at 95%+ accuracy.
  • Object detection v1: trained with just 5 validation images, identifies household objects instantly in real time at 80%+ accuracy.
  • Object detection v2: trained on 110k SKU images, identifies objects of any size in any environment at 95%+ accuracy.
  • Human and object detection: trained on RF-DETR, identifies both in real time. Converted to ONNX runtime and packaged as an Android APK that performs equally well on device.
RF-DETRONNXAndroidPose estimation
PaymentsStablecoins

StablePe Stablecoin payments

A stablecoin payments app built for B2B businesses and remittance, with a waitlist of businesses and individuals.

  • AML Relay API: an automated safety tool that checks a receiver's wallet against official government blocklists such as the OFAC list, stopping illegal payments before they happen.
  • A verification system that reads a wallet's on-chain transaction history to compute a risk score, automatically blocking wallets above 85 and flagging a warning for the rest.
  • Scan dashboard: real time monitoring for researchers and analysts, tracking whale transactions, wallet histories and live activity across the top stablecoins and chains.
BlockchainAMLRisk scoring
SecurityDesktop app

Spectra One tool for every kind of bug hunting

  • An all in one Windows app in Electron and React combining asset discovery, traffic interception and vulnerability scanning, replacing a stack of fragmented CLI tools.
  • A custom MITM proxy in Node.js that intercepts and modifies live HTTPS traffic, using SQLite to handle large request volumes without slowing down.
  • Intercept, Repeater, Intruder and History, plus paid-tool equivalents for free: collaborator URLs, disposable mail and VPN.
  • A full xterm.js terminal with WSL support, so custom Python or Go scripts run inside the app.
ElectronReactNode.jsSQLite
Voicenpm package

Voice OS Multilingual voice assistant

  • A cross platform AI agent in an npm package that automates tasks by voice, supporting 8 languages across the STT and TTS pipelines. 1100+ downloads.
  • Integrated STT (Vosk), TTS (Edge) and an LLM pipeline so the whole loop runs on the user's device.
  • Added document processing, music control through Spotify, and task automation.
VoskEdge TTSLLMnpm
SpeechReal time

Speech to Text Self hosted streaming service

  • Streaming speech to text with Vosk and FastAPI, exposed over WebSocket for real time transcription.
  • Processes 16-bit PCM mono audio at 16kHz straight from the microphone, with no explicit server side buffering.
  • Partial and final transcription streaming, so feedback arrives near real time during live speech.
  • Supports both WebSocket streaming and HTTP file transcription, with codec agnostic decoding through FFmpeg and a fallback decoder.
VoskFastAPIWebSocketFFmpeg
SpeechSynthesis

Text to Speech

  • A text to speech model written in Python, using Microsoft Edge voices.
PythonEdge TTS
03

Education

Oct 2021 to Jun 2024Lucknow

Shri Jai Narain Mishra PG College

Bachelor's in Science, Computer Science. Computer Science, Maths and Physics.

Apr 2020 to Apr 2021Lucknow

Rani Laxmi Bai Memorial School Intermediate

Physics, Chemistry, Maths and Computer Science. 85.6%.

Apr 2018 to Apr 2019Lucknow

Rani Laxmi Bai Memorial School High School

Physics, Chemistry, Maths and Computer Science. 80%.

04

Skills and interests

Programming

JavaScript, Python, React Js, HTML, CSS, SQL, Linux, APIs, Node js, Git and MongoDB.

Languages

Hindi, English, Awadhi and Bhojpuri.

Interests

Chess, football and the internet.

Writing

Writing something.