One-person Staff-level Advisory, Est. 2019
Calm, rigorous machine learning and data work for consequential teams.
I help teams turn ambiguous data and ML problems into robust systems, sharper decisions, and measurable outcomes — without theatrics, office politics, or performative process.
Review My Engagement Terms →Currently
Booking Q4 2026
Based
Taiwan — Working Globally
Engagement Type
Fully Remote; Async-first
The practice
A single senior practitioner, chosen deliberately.
Most ML consultancies are agencies aiming for scale, billable hours, and overhead. I run a single-person office for an entirely different reason: intellectual challenge and tangible impact.
Having built a comfortable financial cushion from my previous engagements, I consider only new engagements in which I can put my expertise and working style to full use. Every client gets my full attention, my honest opinion, and a direct line of communication that never goes through a project manager.
What I help with
High-signal ML leadership without the hype.
Production ML Engineering
I step into half-built systems and turn them into robust production systems. Drawing on staff-level experience building core ML infrastructure at a category-leading vertical online retailer with $400M+ in annual revenue, I design and ship systems that perform under real commercial constraints.
- Core ML infrastructure design
- System rescue & modernization
- Pragmatic build-vs-buy decisions
Modeling That Holds Up
Once ranked 63rd globally on Kaggle, I've spent years solving hard modeling problems in competitive, leaderboard-ranked environments. From CV, tabular, and recommender systems to pragmatic LLM and RL post-training work, I build models optimized for actual business metrics, not vanity benchmarks.
- CV, tabular & recommender systems
- Evaluation & metric design
- LLM & RL post-training
Fractional ML Leadership
I provide staff-level clarity for your AI strategy, grounded in a deep computer science and statistics background. I help technical founders set direction, establish rigorous evaluation methodologies, and debug hard-to-explain model behavior.
- ML roadmap & technical direction
- Technical due diligence
- Statistical debugging & validation
How I work
A small set of beliefs, held consistently.
-
01
Remote and async by design.
I work fully remotely from Taiwan and operate across time zones without friction. No on-site visits, no performative face time. You get focused output delivered in writing — not presence billed by the hour.
-
02
Written, not performed.
The best deliverable is a clear technical memo. Fewer slides, more thinking made visible in code and documentation. If a decision matters, it should survive being read, not just heard in a meeting.
-
03
Evidence first, consensus second.
I'll tell you what the data says and where your system is breaking — plainly, with evidence. Then I'll help you decide what to actually build. I don't optimize for consensus; I optimize for clarity.
-
04
One senior, end-to-end.
You hire me. Not a pyramid. The person doing the work is the person writing the code, reviewing the math, and owning the trade-offs. No handoff to a junior associate you've never met.
-
05
Pragmatic over hyped.
I am allergic to model-bloat. If a well-specified statistical model or a simple ensemble achieves the outcome at a fraction of the cost and complexity, that is what we build. Sophistication is a tool, not a goal.