Founding Applied AI/Systems Engineer

ManaMind; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Equity

Flexible hours

High-trust culture

Job summary

ManaMind is building autonomous agents that take real actions in live games. We’re seeking a Founding Applied ML Engineer to turn multimodal models into reliable agents across Android, iOS and PC.

You’ll design how bots observe the screen, decide what to do next, and recover when real-world behavior diverges from demos. If you want to ship real product and shape how games are tested, this seat is for you.

Qualifications

• Experience building vision-based or multimodal agents.
• Hands-on with vision agents and large multimodal models (LLaVA, CLIP, Flamingo).
• Experience at an AI product startup, ideally from zero to one.

Responsibilities

• Design end‑to‑end game agents linking perception to actions.
• Build cross‑device automation across devices and OS versions.
• Automate critical user journeys and production‑level tests.
• Harden agents for production under real-world conditions.
• Collaborate with QA and engineering teams to align roadmaps.

Skills

Vision systems

Multimodal agents

Computer vision

LLaVA

CLIP

Flamingo

Production ML

Job description

Do you build agents that take real actions in live systems, where reliability and recovery matter more than perfect demos?

Do you want to work close to the metal, deep systems, infrastructure as code, bot and scraping platforms, and low level video streaming?

About us

We're an early‑stage startup built on a simple belief: game developers should be building worlds, not chasing bugs.

We're replacing manual QA with autonomous agents that truly understand gameplay.

Our small, focused team combines deep machine learning research with strong commercial execution, driven to solve some of the hardest problems in game development.

Just over a year in, we've built category‑leading technology, gained real traction, and partnered with some of the world's most storied game studios.

We're backed by top‑tier investors and incubators, including SVV and EWOR.

The role

We are looking for a Founding Applied ML Engineer to own the moment where our models stop predicting and start acting in real games. You'll be the person who takes the multi‑modal model and turns it into reliable agents that tap, swipe, navigate, and verify flows across real devices; Android, iOS, PC.

This role sits at the intersection of ML, automation, and systems engineering: you'll design how bots observe the screen, decide what to do next, and recover when the real world doesn't behave like a demo. If you want your work to live in production, catch real bugs, and influence how an entire industry tests games, this is the seat.

Key responsibilities

• Design End‑to‑End Game Agents

  Build systems that connect perception (pixels, UI, simple state) to concrete actions (taps, swipes, clicks), so agents can reliably drive real games on mobile and desktop.

• Build Cross‑Device Automation

  Develop mechanisms to replay complex user flows across a wide range of devices, OS versions, and aspect ratios without relying on brittle coordinates or hard‑coded timings.

• Automate Critical User Journeys

  Turn core flows—tutorials, core loops, purchases, and other high‑value behaviors—into repeatable automated tests that can run on every build or on demand.

• Harden Agents for Production

  Instrument, debug, and improve reliability under real‑world conditions (slow networks, inconsistent load times, flaky SDKs), and own the quality bar until QA teams trust running these unsupervised.

• Own the Production Standard

  Create and maintain internal eval suites that measure what actually matters.

• Collaborate with Customers

  Work with QA and engineering leads at game studios to understand their workflows, prioritize what to automate next, and incorporate their feedback into the roadmap.

You're a good fit if you…

You've built vision‑driven or multimodal agents using video, not just text or images, with a strong computer‑vision foundation across models. You're hands on with vision agents and VLMs such as LLaVA, CLIP, and Flamingo, and you've applied them in messy, real‑world environments like automation, robotics, autonomy, AV, or complex UI‑driven systems. You're comfortable working closely with QA and testing leads, and you've done this in an AI product startup, ideally at the zero to one stage.

Build things that actually touch the real world

Think in loops, not scripts

You're more interested in building agents that observe → decide → act → recover than recording click macros. You know how to combine simple perception (what's on screen) with control logic (what to do next) so systems stay robust when UIs, timings, or devices change.

Like talking to users as much as to your IDE

You're comfortable jumping on calls with QA / engineering leads, asking blunt questions about their workflows, and turning vague complaints ("this flow keeps breaking") into concrete automation that saves them time.

Bonus: You enjoy games or complex interactive systems

You don't have to be a hardcore gamer, but you're genuinely curious about how interactive experiences are built, broken, and tested; and you like the idea of agents learning to navigate them.

What's on offer

High trust, high impact: ship real product fast, work directly with founders.

Equity

Meaningful equity ownership. You'll share in the upside you help create.

Flexible hours, and a culture built on trust and output.

Get on board. Apply now.

Think you have the skill and drive to thrive in this role? We can’t wait to meet you and get a taste of your work.