AI Systems & ML Engineering Industry Expert

TripleTen•New York City, NY

10d•Remote

About The Position

TripleTen is a career learning platform for tech professionals and beginners aiming for higher-paying tech and AI roles. Launched in 2020, with programs across the US and Latin America, over 7,500 people have completed our programs. Our team is fully remote and globally distributed. In 2026, we expanded with a second tier of programs for existing tech professionals: AI Systems Engineering, AI & Machine Learning, and Forward Deployed Engineering. These advanced programs are designed for mid/senior engineers, and we are seeking a select number of Industry Experts to establish the technical standard for each. This role is focused on judgment and critique, similar to a Staff or Principal engineer evaluating designs, rather than teaching or content creation. The curriculum is developed by a separate team. Your expertise will be crucial as students design and defend real-world systems. You will challenge their decisions rigorously, providing the kind of critique expected in senior engineering circles, and ensuring the program's value for experienced professionals. Each program consists of five production-level projects, culminating in a live defense. Responsibilities include sitting on final project defenses, reviewing deployed systems, distributed-systems capstones, agentic architectures, or client-facing delivery packages against a rubric, and conducting the defense while offering structured, senior-level critique. You will also chair mock review boards and executive-panel presentations, including architecture review boards, model and system reviews, and executive go/no-go presentations. Additionally, you will host one to two live sessions per month focusing on the design and decision-making aspects of your domain, such as system splits, failure modes, and trade-offs. You will also set the technical standard for instructors delivering weekly content and serve as their escalation point for complex design decisions. This role does not involve weekly coverage, office hours, or first-line support.

Requirements

8+ years of professional engineering experience.
Currently at senior/staff/principal level or equivalent (Staff/Principal Engineer, Senior/Staff ML Engineer, Solutions Architect, Forward Deployed Engineer, technical lead).
Shipped systems that run in production at real scale as an employee in an engineering role.
Ability to explain why a decision was made, not just how it was implemented.
Ability to diagnose and critique someone else's architecture live, on a call, without preparation.
A public technical footprint: GitHub, conference talks, a book or O'Reilly/Manning title, a technical blog, open-source work, or documented mentorship.
Strong English (C1+).
Time zone: Americas strongly preferred (US / Canada / LatAm).
Sessions land in US afternoon and evening hours.
Comfortable using AI tools in day-to-day technical work.
Domain depth in one of the following tracks: AI/ML Engineering, AI Systems Engineering, or Forward Deployed Engineering.

Nice To Haves

Have run technical sessions in some form: internal tech talks, conference workshops, engineer onboarding, or mentoring.
Hands-on ownership of an eval or observability stack in production, not just usage of one.
Experience being the primary technical resource embedded with a customer team (for the FDE track).

Responsibilities

Sit on final project defenses.
Review deployed systems, distributed-systems capstones, agentic architectures, or client-facing delivery packages against a rubric.
Run the defense and give structured, senior-level critique.
Chair mock review boards and executive-panel presentations.
Host one or two live sessions a month on the design and decision layer of your domain.
Set the technical standard for the instructors running weekly delivery.
Act as an escalation point for instructors on hard design calls.