AI Systems & ML Engineering Industry Expert in London

TripleTen is a career learning platform for tech professionals and complete beginners ready to move into higher-paying tech and AI roles. We launched in 2020, we run programs across the US and Latin America, and 7,500+ people worldwide have completed one. Our team is fully remote and globally distributed.

In 2026 we opened a second tier of programs for people already working in tech: AI Systems Engineering, AI & Machine Learning, and Forward Deployed Engineering. We're launching three advanced engineering programs for working mid/senior engineers, and we're looking for a small number of Industry Experts to set the technical bar in each of them.

This is not a teaching or content-authoring role. The curriculum is built by a separate team of senior authors. What we need from you is judgment: the kind of call a Staff or Principal engineer makes when they look at a design and know, in thirty seconds, that the service split is wrong, the eval is measuring the wrong thing, or the scope will not survive contact with a client.

Our students design and defend real systems. Your role is to challenge those decisions the way you'd challenge a peer's — and to be the name that tells an experienced engineer this program is worth their time. Each program is a chain of five production-level projects, and every project ends in a live defense.

Responsibilities include:

• Sitting on final project defenses.
• Reviewing a deployed system, a distributed-systems capstone, an agentic architecture, or a client-facing delivery package against the rubric — then running the defense and giving structured, senior-level critique.
• Chairing mock review boards and executive-panel presentations.
• Hosting one or two live sessions a month on the design and decision layer of your domain.
• Setting the technical standard for the instructors running weekly delivery, and acting as their escalation point on hard design calls.

You are not on the hook for weekly coverage, office hours rotations, or first-line questions. A separate team handles that.

Who you'd be reviewing:

• Working engineers and tech professionals, not complete beginners.
• Middle or senior developers, platform and data engineers, network and infrastructure people, security and incident-response specialists.

Requirements:

• 8+ years of professional engineering experience, currently at senior/staff/principal level or equivalent.
• Experience shipping systems that run in production at real scale.
• Ability to explain why a decision was made, not just how it was implemented.
• 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).
• Comfortable using AI tools in day-to-day technical work.

Domain depth — one of three tracks:

• AI/ML Engineering.
• AI Systems Engineering.
• Forward Deployed Engineering.

Nice to have:

• Experience running technical sessions in some form.
• Hands-on ownership of an eval or observability stack in production.
• Experience being the primary technical resource embedded with a customer team (for the FDE track).

A genuinely small commitment: 4–10 hours a month, slots booked about two weeks ahead, pausable at any time. Hourly payment, negotiable depending on experience, track, and scope. Fully remote, with a small international team and no micromanaging.