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01.

About

01
Jaskaran Singh

Senior Android Engineer.Fintech, mobile platforms, and applied AI.

Toronto-based mobile engineer with 5 years in fintech, Kotlin/Compose depth, and current code-model evaluation work.

5 years 30+ features Open senior roles
Primary stack Kotlin

Compose, coroutines, MVVM, release quality.

Product space Fintech

Payments, lending, trust, reliability.

Current edge LLMs

Evaluation, fine-tuning, model quality.

Profile Senior Android and applied AI.
Jaskaran Singh portrait
Location Toronto, Canada
Focus Android + AI
Senior Android

Kotlin, Compose, Flutter.

Fintech background

Mobile banking, lending, and merchant payments.

Current AI work

LLM evals and model quality.

I build Android applications that people trust with their money. Over the last five years I've shipped production mobile software at Comviva and Rupeek — across mobile banking, merchant payments, and gold-loan product flows — and contributed to the release engineering, performance and security practices those products depend on.

My day-to-day work lives in Kotlin, Jetpack Compose and Flutter, with deep exposure to MVVM, dependency injection, coroutines, and the CI/CD surface around them — Jenkins, Firebase distribution, SonarQube, Checkmarx. I care about codebases that stay readable under pressure and teams that ship without breaking trust.

Since July 2024 I've also been working as an Advanced Coder in AI Training at Outlier, improving code-generation models through prompt design, RLHF-oriented review, testing workflows, and failure analysis across Kotlin, Java, Python, C, and C++ tasks.

I hold an M.Eng in Electrical & Computer Engineering from the University of Windsor and a B.Tech from NIT Jalandhar. I'm based in Toronto and open to senior engineering roles — on-site, hybrid, or remote.

Jaskaran Singh
0 Years
Experience
0 Features
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Impact snapshot
A cleaner proof layout with no graph styling. Fast to scan, but calmer and more premium.
Reach 5
Years of professional Android and mobile product work.
Shipping 30+
Android features delivered across production teams.
Efficiency 20%
Crash reduction reported in Mobiquity Pay delivery work.
Kotlin, Compose, Flutter, LLM evals, CI/CD and release quality.
Profile perspective

Review the profile by hiring priority.

Short view for hiring, mobile, or AI teams.

Click a mode to reframe the story
A senior mobile engineer who already understands production trust.

This profile is strongest when the role needs real user scale, high shipping confidence, and a candidate who can speak both product outcomes and technical choices.

Hiring manager lens
Primary signal Production scale without hand-wavy claims

Fintech experience is grounded in user reach, release ownership, and concrete improvement metrics.

How to pitch it Bridge candidate

Rare mix of Kotlin/Compose depth and current LLM evaluation work makes this a credible mobile plus AI hire.

Best conversation starter What kind of team benefits most

Any product organization where reliability, delivery pace, and thoughtful technical judgment matter as much as feature velocity.

5 yrsProfessional mobile engineering experience
50+Features across Rupeek, Mobiquity Pay, and PayPlus
TorontoOpen to hybrid, remote, and senior roles
02.

Experience

02

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Career timeline

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A structured view of the experience, presented as a sequence rather than a static list.

2024 - Present
Outlier AI
Building evaluation systems for code-generation models with an engineering-first lens.
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    03.

    Projects

    03
    3 projects shown
    Selected case studies

    Review representative work.

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    01 / 03 · Life-Capture Notes
    01 / Featured Project
    Life-Capture Notes
    Flutter-based smart note-taking app supporting text, voice, and image capture with location-based reminders, recommendations, AI-powered note summarization, automatic note generation, and personalized suggestions.
    Flutter Python PostgreSQL Google Maps API AI Integration
    Life-Capture Notes app screenshot
    02
    Anti-Drowsiness Driver Assistant
    Real-time computer vision system detecting driver drowsiness via facial landmark analysis. Triggers real-time alerts and supports intelligent suggestions for nearby amenities, with data collection for improved user assistance.
    Python OpenCV Computer Vision AI Model Training Data Analysis
    Anti-Drowsiness system screenshot
    03
    Video on Demand Platform
    Hotstar-inspired streaming desktop application built with Java socket programming and a normalised MySQL backend. Supports concurrent multi-user streaming sessions, authentication, and a content management dashboard.
    Java Socket Programming JDBC MySQL
    Video on Demand platform screenshot
    04.

    Writing

    04
    05.

    Stack

    05

    The tools I reach for every week — grouped by surface. Bolded rows are the primary stack I work in daily; the rest are things I've used seriously on production projects. Year counts reflect hands-on shipping time, not exposure.

    Mobile 10 tools
    • Kotlin 5 yrs · daily
    • Jetpack Compose 3 yrs · daily
    • Android SDK 5 yrs · daily
    • Coroutines & Flow 4 yrs
    • Flutter / Dart 2 yrs
    • Kotlin Multiplatform 2 yrs
    • Retrofit, Room, OkHttp 5 yrs
    • Dagger 2 / Hilt 4 yrs
    • MVVM, Clean Architecture 5 yrs
    • Espresso, JUnit 5, MockK 4 yrs
    AI & ML 7 tools
    • LLM fine-tuning 2 yrs · daily
    • RLHF & reward modelling2 yrs · daily
    • Prompt engineering 2 yrs · daily
    • Evaluation frameworks 2 yrs
    • Python 4 yrs
    • Computer vision 2 yrs
    • OpenCV, dlib 2 yrs
    Backend & Data 7 tools
    • Java 5 yrs
    • REST APIs 5 yrs · daily
    • Firebase suite 4 yrs
    • PostgreSQL 3 yrs
    • MySQL 3 yrs
    • Google Maps API project use
    • Flask 2 yrs
    Delivery & Quality 8 tools
    • Git, GitHub, Bitbucket 5 yrs · daily
    • Jenkins CI/CD 4 yrs
    • SonarQube, Checkmarx 3 yrs
    • Firebase Crashlytics 4 yrs
    • Gradle, Fastlane 4 yrs
    • JIRA, Agile / Scrum 5 yrs
    • Figma hand-off 4 yrs
    • Play Console & Keystore mgmt 5 yrs
    06.

    Approach

    06
    01
    Execution
    End-to-end mobile delivery
    I work across architecture, implementation, release quality, and production refinement so delivery remains strong after launch.
    Kotlin Compose Ownership
    02
    Reliability
    Reliability and release discipline
    CI/CD, crash monitoring, rollout control, and security checks that help teams ship with confidence and operate with less risk.
    Jenkins Quality gates Release flow
    03
    Curiosity
    Applied AI for mobile products
    I am most effective on products that combine strong Android execution with model evaluation, iteration speed, and practical AI use.
    LLMs Evals On-device AI
    07.

    Current focus

    07
    At work
    LLM evaluation frameworks
    Working on prompt design, testing frameworks, and code review for code-generation model quality at Outlier.
    Independent work
    On-device AI experiments
    Exploring local inference on Android with attention to latency, packaging, and user experience.
    Research
    Agent systems and evaluation tooling
    Following how agent frameworks, retrieval systems, and evaluation tooling are maturing in practice.
    Open to
    Senior Android and applied AI roles
    Full-time or contract opportunities in Toronto, hybrid, or remote environments.
    Location
    Toronto, Ontario
    Eastern time. Comfortable working across North America, Europe and India — most of my career has been distributed.
    Focus
    Mobile products shaped by AI
    Most interested in products that place useful model capability directly in customer workflows.
    08.

    FAQ

    08
    Both. I'm actively looking for full-time Senior Android / AI-ML roles in Toronto or remote, and I also take on select contract engagements — especially for teams needing LLM evaluation frameworks or Compose migration expertise.
    I'm based in Toronto (Eastern Time, UTC−5). I work comfortably with teams across North America, Europe, and India — most of my career has been on distributed teams.
    My deepest expertise is Android + AI training, but I've shipped Flutter to both platforms, built Flask/Java backends, and integrated REST APIs across the stack. I ramp quickly on unfamiliar tech when a project needs it.
    My Outlier work keeps me close to code-generation model evaluation. For Android, I follow the Jetpack Compose roadmap, read Android engineering blogs, and experiment with on-device inference patterns using Gemini Nano in side projects.
    Email is best — jaskaran.chana1302@gmail.com. LinkedIn DMs also work. I typically respond within a business day.
    09. Contact

    Open to the right opportunity.

    I'm currently considering senior Android and AI/ML engineering roles — full-time or contract, based in Toronto or remote. If your team is building a meaningful product and this profile aligns with the role, I would be glad to continue the conversation.

    jaskaran.chana1302@gmail.com
    Professional summary

    Senior Android Engineer based in Toronto with experience across fintech delivery, platform quality, and applied AI evaluation. Best suited to teams that value clear engineering judgment, production trust, and strong product execution.

    Meeting availability
    Toronto time
    Mon
    10:00 - 12:00
    14:00 - 16:00
    Wed
    09:30 - 11:30
    15:00 - 17:00
    Fri
    10:00 - 13:00
    Remote-friendly
    A practical starting point for introductions, screening calls, or technical discussions.
    ~/jaskaran — zsh
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