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Elite track
Turn frontier skill into a frontier offer.
Convert everything you have built into an elite AI role: AI/ML system-design interviews, a public portfolio that gets noticed, the real hiring pipeline at frontier labs, top product companies, well-funded startups, and global remote teams, technical writing and communication, open-source contribution and visibility, and compensation and negotiation. You leave with a shipped portfolio product and a rigorous public technical writeup. Bridges to professional practice and software-engineering communication.
Week by week
Every week unlocks the next. Concepts route you to free, world-class material; projects turn that knowledge into something deployed.
Week 1
The interview that decides senior AI offers: scoping an ML problem, designing data pipelines, feature stores, training and serving infrastructure, and monitoring, then defending the tradeoffs out loud under time pressure.
Builds on: nothing, start here
Week 2
Turning a project into evidence: framing a hypothesis, running clean ablations, and tracking every run — config, code commit, metrics, artifacts — so a result is reproducible and a reviewer trusts your numbers.
Builds on: AI / ML System-Design Interviews
Week 4
A portfolio is a product: a small number of deep, shipped, publicly hosted projects with live demos, clean repos, and honest writeups beat a long list of tutorials. Curation, presentation, and proof of real work.
Builds on: Running Experiments, Ablations & Tracking
Week 6
Writing that makes your work legible: a clear claim, evidence, and honest limitations; explaining a hard idea simply; and the interactive, visual standard set by Distill. Communication is the multiplier on every project you ship.
Builds on: Building a Portfolio That Gets Noticed
Week 7
A career mandate: your portfolio is itself a product, and a hiring manager judges it the way a user judges any product — in seconds. Build and launch a portfolio site that presents a small number of your deep, shipped AI projects with live demos, clean repos, honest writeups, and real metrics. This is not a resume page: it is a directly deployable, hyperscalable, hyper-usable product with real public hosting, CI/CD, observability, accessibility, security headers, and full marketing polish. Treat curation as ruthlessly as engineering — three projects shown well beat ten shown badly. The portfolio must load fast, be reachable by anyone, and make a stranger want to talk to you. Ship it as a real product.
Why it matters: For AI roles, a public portfolio of deep, shipped projects is one of the strongest hiring signals, because it lets a hiring manager verify real work instead of trusting a resume. A builder who can present curated, hosted, well-documented projects stands out in the elite hiring pipeline, where take-home quality and demonstrable shipped work weigh heavily.
A publicly hosted portfolio product with a stable URL and a polished, fast, accessible UI, plus a public repo: the portfolio site, deep writeups of a curated set of AI projects each with a live demo link and real metrics, CI/CD on every commit, observability, security headers, a README documenting the build and design decisions, and a short pitch of the portfolio itself as a product.
Market signal, who wants thisIn the 2026 AI hiring market, demonstrable shipped work is a primary screening signal: field-guide research into AI-engineering hiring shows take-home projects and write-up quality are weighted heavily, and recruiters respond to verifiable public work over cold resumes. A portfolio of deep, hosted projects is what moves a candidate from the application pile into a real conversation.
Week 8
Earning a public track record: scoping a first contribution, working with maintainers, and building visibility through real PRs to AI libraries. Open source is a hiring signal a recruiter can verify without trusting your resume.
Builds on: Technical Writing & Communication
Week 9
How frontier labs, top product companies, well-funded startups, and global remote teams actually hire: research-engineer interview loops, take-home projects, the weight of referrals over cold applications, and how to enter the pipeline.
Builds on: Open-Source Contribution & Visibility
Week 11
Closing the offer well: how AI compensation is structured (base, equity, sign-on), how to benchmark a number, and how to negotiate respectfully from leverage instead of accepting the first figure on the table.
Builds on: The Elite AI Hiring Pipeline
Week 12
A career mandate: take one frontier project you have built — a fine-tuned model, an interpretability tool, an inference system, a safety evaluation — and publish a rigorous, public technical writeup of it. This is the artifact that demonstrates research-grade communication: a clear claim, a reproducible method, honest results with ablations, and stated limitations, written so a frontier-lab engineer takes it seriously. Publish it as a launched product: a real public page with its own stable URL, fast and accessible, with the code and data to reproduce it linked, and presentation polish to the standard set by Distill. A writeup nobody can find or reproduce does not count. Ship it as a real product.
Why it matters: Research-grade technical communication is a differentiator in elite AI hiring: frontier and research-adjacent roles expect a candidate to read, reproduce, and clearly write up results. A builder who can publish a rigorous, reproducible writeup demonstrates exactly the communication and methodology those roles assume, and creates a durable, verifiable public signal of frontier-level work.
A publicly hosted technical writeup with a stable URL and a fast, accessible reading experience, plus a public repo: the writeup itself with a clear claim, method, results, ablations, and limitations, the code and data needed to reproduce the central result, CI/CD on every commit, and a README pointing to the reproduction steps.
Market signal, who wants thisClear public technical writing is a recognized signal in AI hiring and research culture: venues like Distill established that rigorous, well-communicated research artifacts are real contributions, and frontier-lab interview guides emphasize the ability to read, reproduce, and communicate results. A reproducible public writeup gives a candidate a durable, verifiable demonstration of frontier-level methodology and communication.
What's next
Each track stands alone, so there's no wrong order. If you want a suggestion, this one pairs well next.