Matchii is the new way to hire agencies: matched, not browsed.
Hiring an agency today is a slog: 20+ quotes, 40+ hours of vetting, and a gut-feel pick that's wrong about half the time. Matchii makes it feel like booking the perfect flight; describe what you need, the right team appears, work begins. Human, AI-native, or hybrid. We match. We back the outcome. Behind the scenes, it's two products on one platform: a matched marketplace for the people doing the hiring and an operating system that the agencies run their whole business on. Underneath both is a data layer, the largest dataset of real services pricing and outcomes anywhere, that makes every match smarter than the last. The timing is the whole point. The $500B+ global agency services market is old and broken, and AI just blew the supply side open: 100+ AI-native services launched in the past year alone, with no platform connecting buyers to the new shape of supply. That gap has been open for years. We're building the company that fills it.
Role summary
This role develops and deploys machine learning systems that drive matching, recommendations, pricing, automation, and other AI-powered experiences across the platform.
Working closely with founders, product, engineering, and data teams, this role transforms data into intelligent products, integrates machine learning capabilities into production systems, and helps establish the foundations for Matchii's AI-native platform.
As an early engineering hire, this role will have significant influence over our AI strategy, data infrastructure, and the evolution of our intelligence layer.
What you'll own
Build and deploy AI-powered features across matching, recommendations, pricing intelligence, and workflow automation.
Develop, evaluate, and improve machine learning and LLM-based systems using real-world product and marketplace data.
Design, build, and optimize AI-powered pipelines that convert customer briefs into structured scopes of work (SoW), recommendations, and execution-ready workflows.
Own the end-to-end lifecycle of ML systems, from data preparation and model development to deployment, monitoring, evaluation, and continuous improvement.
Bridge the gap between AI prototypes and production systems by building reliable, scalable, and measurable machine learning workflows.
Work closely with founders, product, engineering, and data teams to bring AI capabilities from idea to production.
Design and maintain data pipelines, model evaluation frameworks, and inference infrastructure.
Optimize models and systems for accuracy, reliability, performance, scalability, and business outcomes.
Maintain high engineering standards through testing, monitoring, documentation, and code reviews.
Help shape Matchii's AI capabilities, data foundations, and intelligence layer as an early member of the team.
Who we're looking for
5+ years of engineering experience, with 3+ years building and deploying ML and LLM systems in production.
Applied LLM & ML expertise: Deep hands-on experience with RAG, structured outputs (e.g., turning briefs into SoWs), matching algorithms, or recommendation systems.
End-to-End MLOps: Proven track record of designing data pipelines, robust model evaluation frameworks, and scalable inference infrastructure.
From Prototype to Production: A pragmatic builder who can rapidly bridge the gap between experimental AI concepts and reliable product features.
Founding Mindset: Highly autonomous, comfortable with ambiguity, and driven to partner with founders to build Matchii from the ground up.
Why this, why now
You won’t just be tuning hyperparameters or maintaining someone else's legacy code. As an early champion of Matchii's intelligence layer, you will work directly with the founders to define our data architecture, shape product direction, and build the proprietary matching engines from the ground up. You’ll have a front-row seat and a heavy hand in how we turn unstructured marketplace data into an automated, scalable ecosystem.
We are at a critical inflection point. As we build the foundations to scale Matchii globally, your technical choices will directly dictate our marketplace efficiency and durable competitive advantage. If you want to move fast, ship AI features that solve real-world business problems daily, and deeply influence the engineering culture of a fast-growing startup—this is the moment.
How we hire
Intro call (30 min).
Founder call: the market and what you've closed.
Assessment.
References & offer.
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