Founding Machine Learning Engineer

About Matchii

Matchii is a matched marketplace for hiring agencies. The platform connects clients with the right service providers (human, AI-native, or hybrid) and provides agencies with an operating system to run their business. Behind both is a data layer containing the largest dataset of real services pricing and outcomes, making every match smarter than the last.

The $500B+ global agency services market is fragmented and outdated. AI has opened up the supply side with 100+ AI-native services launched in the past year alone, creating a gap between new suppliers and traditional buying processes. Matchii is building the platform that bridges this gap.

The Role

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, you will transform data into intelligent products, integrate machine learning capabilities into production systems, and help establish the foundations for Matchii's AI-native platform. As an early engineering hire, you will have significant influence over AI strategy, data infrastructure, and the evolution of the 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

• Experience: 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 data architecture, shape product direction, and build proprietary matching engines from the ground up. You'll have a front-row seat and a heavy hand in how the platform turns unstructured marketplace data into an automated, scalable ecosystem.

Matchii is at a critical inflection point. As the foundations are built to scale globally, your technical choices will directly dictate 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.

Hiring Process

• Intro call (30 min)
• Founder call: the market and what you've closed
• Assessment
• References & offer