Real production-grade experience · Application-gated
You can't get experience without a job. You can't get a job without experience. We build the experience that breaks it.
Spend 8–16 weeks building the same kind of AI systems banks and wealth managers ship — in a training environment that mirrors their architecture and standards, on synthetic data — guided by the senior engineers and scientists who do this for a living. Whether you come from a CS background or a finance one, you walk away with production-grade work, a portfolio recruiters respect, and proof an employer can verify.
The problem
A degree alone no longer differentiates you.
You're stuck in the cold-start paradox: every role wants experience, and no one will give you the experience to get it. Meanwhile AI is quietly absorbing the very junior work that used to be how people broke in. The people who win the next decade are the ones who can show, not claim, that they can do the work.
What this is
Real work, real review, proof you can verify.
Ledgerline is a paid educational fellowship run by a company that builds production AI for banks and wealth managers on a SOC 2 Type 2 platform. You build the same kind of systems they ship — in a dedicated training environment that mirrors real fintech-AI architecture and standards, on synthetic data. You never touch client systems or real customer data; what you touch is the craft.
Your work is reviewed by senior engineers and scientists who do this for a living. And everything you build is backed by a verification page an employer can actually check.
Fellowships are application-gated. We admit people we're confident can finish production-grade work and prove it.
Two tracks
Which one is you?
Engineering Track
For CS and data-science students and grads who can already code but can't get real experience — especially anyone aiming at fintech, quant, or AI engineering. You build the systems: production-grade AI features, merged code, architecture you can defend.
Skill floor: you can write code. ML scaffolding is provided where you need it.
FinTech Track
For finance, econ, and business students and grads — IB, sales & trading, asset and wealth management, fintech, risk, corporate finance — who have some Python. Banks are racing to put AI into KYC, AML, compliance review, and portfolio analysis, and can't find people who understand both sides. You build the rare ability to work between finance and AI.
Skill floor: you can load a CSV into pandas, write a for-loop, and call a library function. Heavy ML is scaffolded; every deliverable gets expert review.
Not for: certificate-collectors, people who want to live inside model internals (that's the Engineering Track), or guaranteed-offer shoppers.
The tiers
One ladder, two tracks.
Same prices and structure across both tracks; the deliverables flex to fit your track. Each tier is priced around the weeks of senior-reviewed, portfolio-ready work you ship — less than a typical immersive bootcamp, and refundable for 14 days, no forms.
Build
Get real, reviewed work into the world and prove it.
- Production-grade work, shipped and reviewed by senior engineers (async senior code review)
- A verification page an employer can check
- A spot at Demo Day
Accelerate
Everything in Build, plus mentorship and interview reps that sharpen how you present your proof.
- Everything in Build
- 1:1 mentorship with a senior mentor
- Two mock interviews with real feedback
- A career asset pack: portfolio site, LinkedIn, and a recruiter-reviewed résumé
- Demo Day
Scholar
The deepest tier: independent technical work, co-supervised by a researcher.
- Everything in Accelerate
- An independent technical paper or report you author and own — coaching and editorial review only, never ghostwritten and never a guaranteed publication
Looking for ongoing, invite-only senior guidance beyond a cohort? Ask us about Concierge (invite-only).
Your mentors
For a new program, your proof of quality is who reviews your work.
Lona Yu
Former Amazon applied scientist in Amazon's Customer Trust org (fraud and abuse). Her anomaly-detection and anti-money-laundering research was named one of Amazon Science's ten most-viewed publications of 2024 and presented at WSDM 2024. Founder-in-Residence at AI2 Incubator.
Wealth-management mentor
A CFP® professional (Series 66) with years of experience as a private wealth manager and regional vice president at established U.S. wealth-management firms. Co-mentors the finance side.
Joanna Fang
A computer scientist and published researcher in human-computer interaction — the study of how people and technology work together — at Virginia Tech. Volunteers her time to help build and run the Ledgerline fellowship.
How it works
Ship real work, get it reviewed, walk away with proof.
Remote, on your schedule
Plan on about 10–15 hours a week.
Application-gated
We admit people we're confident can finish production-grade work and prove it, and we keep cohorts small.
Cohort-based
You build alongside peers and finish on Demo Day — a session where you present your project to mentors and invited engineers.
An 8–16 week arc
Depending on your tier: ship real work, get it reviewed round by round, and walk away with proof.
The fine print, in plain English
- This is education, not employment. You join as a Fellow — not an intern, employee, or job-holder — and you don't become one through the program. Tier names describe how deep the program goes, not a title you earn.
- You build in a training environment that mirrors production standards on synthetic data. You never access clients' systems or real customer data.
- We sell real experience and verifiable proof — not jobs, offers, referrals, or placements. Nothing here implies a guaranteed outcome.
- Nothing in the finance track implies licensing, Series exams, or registered/financial-advisor status.
- Research and paper work is coaching and editorial only — your work, your credit, no guaranteed publication.
- 14-day full refund, no forms.
- Employer verification answered within 48 hours.
How to join
There's no checkout here — fellowships are application-gated, so we talk first.
Apply
A short form: who you are, your track, the tier you're eyeing, and why.
Fit call
A quick conversation to make sure the fellowship is right for you.
Start
If it's a match, we send an invoice and you begin with the next cohort. (14-day full refund still applies once you start.)