Open to opportunitiesSoftware Engineer · ToshibaSilicon Valley · on-site

Keegan PaulColaco.

Where bits meet magnetism.

Software Engineer with 3+ years building firmware-validation and performance tooling for Toshiba's SMR and Hybrid-SMR hard drives — now pushing toward next-generation SSDs, with published deep-learning research and a working knowledge of modern AI on the side.

0.54
CGPA — BTech CSE
0+
Years — HDD firmware
0
Springer paper
0
Hackathon podiums
Keegan Paul Colaco
7,200RPM
C / C++PythonSMR HDD firmwareStress testingwxWidgetsLinuxGit / SVNFIO · VDBenchPerformance analysisYOLOv8Deep learningData visualisation日本語 · JLPT N5C / C++PythonSMR HDD firmwareStress testingwxWidgetsLinuxGit / SVNFIO · VDBenchPerformance analysisYOLOv8Deep learningData visualisation日本語 · JLPT N5
01About

An engineer at the lowest level.

Keegan is a Software Engineer in Toshiba's HDD division, where he's spent the last three-plus years on the unglamorous, high-stakes work that keeps your data safe: validating the firmware inside SMR and Hybrid-SMR hard drives, and building the tooling that proves it's ready to ship.

That means stress-testing drives for hours on end, turning raw failure dumps into something a developer can read, and benchmarking the performance metrics that define a drive's character. He's now setting his sights on next-generation SSDs.

He came up through SRM with a 9.54 CGPA and a software-engineering specialisation, picked up a few hackathon podiums along the way, and published deep-learning research under Springer. Off the clock he's tracking the AI landscape and chipping away at Japanese.

Spec sheet
REV · 2026
ROLE
Software Engineer
DIVISION
Toshiba · HDD
BASED
Bengaluru, IN
ORIGIN
Goa, IN
DEGREE
BTech CSE · 9.54
STACK
C/C++ · Python
LANGUAGES
EN · 日本語 N5
STATUS · OPEN TO OPPORTUNITIES
02Expertise

What I'm good at.

From firmware that can't fail to models that can see — four areas where the work gets interesting.

01

Firmware Validation

Core role · Toshiba

Stress-testing SMR & Hybrid-SMR SATA drives — long-running I/O and zone-operation workloads that surface firmware defects before they ever reach a customer.

02

Performance Engineering

FIO · VDBench

Benchmarking the metrics that matter, then building the CLI and web tools that parse, visualise and make sense of mountains of HDD performance data.

03

Debug Tooling

C++ · wxWidgets

A Windows GUI debugger that turns raw failure dumps pulled off a drive into something an engineer can actually read — cutting firmware debug time.

04

AI / Machine Learning

Published research

Peer-reviewed YOLOv8 work under Springer, plus a working grasp of neural nets, LLMs and RAG — applying deep learning to real-world detection problems.

03The platter · 3D

Inside the drive.

Keegan's day job lives at the lowest level of storage — where firmware meets spinning magnetic media. Here's that world, rendered in real time: drag to orbit, cut the power, toggle the track map, or fire a seek.

04Experience

The work.

Three-plus years at Toshiba, and the tooling that came out of it.

Software Engineer — HDD Division

Toshiba Software India Pvt. Ltd.

Current

Jan 2023 — Present

Bengaluru, India

  • Develop and maintain stress-testing software that validates firmware features of SMR and Hybrid-SMR SATA hard drives.
  • Contributed to a GUI-based HDD debugging tool that measurably improved firmware-debugging efficiency.
  • Work hands-on with performance-benchmarking tools to analyse the key metrics that define a drive.
  • Build scripts and tooling for parsing, visualising and analysing raw HDD performance data.
Selected tooling
C · Linux

HDD Stress-Testing Tool

A Linux stress-testing tool in C that validates SMR HDD firmware by hammering it with hours of I/O and zone-operation workloads — catching defects so releases ship stable and robust.

  • SMR firmware validation
  • I/O & zone workloads
  • Long-duration soak tests
C++ · wxWidgets

HDD Snapshot / Debug Tool

Windows GUI features built on the wxWidgets framework that let developers analyse firmware data extracted from HDD failure dumps — making the un-readable readable.

  • Failure-dump analysis
  • Native Windows GUI
  • Faster firmware debug
FIO · VDBench

HDD Performance Tool

Studied benchmarking tools like FIO and VDBench to evaluate drive performance, then built CLI and web tools to parse, visualise and analyse the data they produce.

  • Benchmark evaluation
  • CLI + web tooling
  • Performance visualisation
Keegan at the Golden Gate Bridge, San Francisco
INTERNATIONAL BUSINESS TRAVEL · USA
05On-site · Silicon Valley

From Bengaluru to the Bay.

The work doesn't stay in one timezone. Keegan collaborates closely with Toshiba's US counterparts — and has been on the ground in California, from the Golden Gate to the Stanford quad — bridging an Indian engineering team, a Japanese multinational and a Silicon-Valley partner.

Golden Gate · San Francisco
Keegan at the Memorial Arch, Stanford University
Stanford University

A genuinely global engineer

One foot in three countries — an Indian engineering base, a Japanese multinational, and a Silicon-Valley partner. It's a workflow built for collaboration across timezones, languages and cultures.

  • India

    Based in Bengaluru — engineering home base.

  • USA

    On-site collaboration in California · Silicon Valley.

  • Japan

    Japanese multinational employer · JLPT N5 certified.

06Research & AI

Beyond firmware — machine learning.

Peer-reviewed deep-learning research, and a genuine, hands-on interest in where modern AI is heading.

Published · Springer Nature

DOI 10.1007/978-3-031-68905-5_10

Development of a Pothole Detection System Using Deep Learning Techniques and Depth Estimation

Deep Sciences for Computing and Communications · Communications in Computer and Information Science (CCIS, vol. 2176)

Peer-reviewed research that uses deep learning to detect potholes and estimate their depth from imagery — a real-world computer-vision system, assessed on a purpose-built preprocessed dataset.

Read on SpringerLink YOLOv8Depth estimation
pothole · 0.94
pothole · 0.87
crack · 0.71
YOLOv8 · INFER
Working knowledge

Core ML foundations

Supervised & unsupervised learning — classification, regression and clustering.

Neural networks & deep learning

Architectures, and how modern language models are trained and fine-tuned.

Large Language Models

Their capabilities, limitations and real-world applications across domains.

Retrieval-Augmented Generation

Grounding LLMs in external knowledge to improve response accuracy.

Generative AI & prompt engineering

Following the landscape — generative models and how to steer them well.

AI for software & automation

Applying AI tooling to solve real problems and streamline workflows.

07Recognition

Awards & education.

Honours & awards

The Hult Prize

Second Runner-Up

Mar 2022

MozoHack 3.0

First Runner-Up

Feb 2022

ThinkTech 2k21

Winners

Nov 2021

Hack With Us

First Runner-Up

Oct 2021

SRMIST Merit Scholarship

Performance-based award — ₹43,750

Jul 2021

Education

BTech — Computer Science Engineering

2019 — 2023

SRM Institute of Science and Technology

CGPA 9.54 · Specialisation in Software Engineering (Agile, Software Quality Assurance)

Chennai, India

Higher Secondary (HSC) — Science

2019

Loyola Higher Secondary School

78.5%

Goa, India

SSLC — Class 10

2017

Loyola High School

89%

Goa, India

08Contact

Let's build something reliable.

Hiring for storage, firmware, performance or applied ML — or just want to compare notes on where AI is going? The fastest way to reach me is a message.

  • SSD & next-generation storage engineering
  • Firmware validation & performance tooling
  • Applied AI / machine-learning engineering
  • Based in Bengaluru — open to relocation