Lead AI & Data Infrastructure Engineer

Matium is building a digital ecosystem for manufacturers, producers, recyclers, distributors, and traders of raw materials. The Lead AI & Data Infrastructure Engineer will own the data architecture and analytics layer, developing systems and models to drive marketplace intelligence, pricing optimization, and decision-making.

Responsibilities:

• Design and deploy machine learning models that power Matium’s supply–demand matching engine
• Develop algorithms that identify optimal buyer–seller pairings across fragmented industrial markets
• Build AI systems that improve auction design, bid aggregation, and price discovery
• Create predictive models for demand forecasting, pricing signals, and market timing
• Continuously improve model performance as transaction data scales
• Architect scalable data pipelines that ingest marketplace, logistics, pricing, and transaction data
• Build a unified data layer supporting analytics, AI models, and internal decision systems
• Implement real-time data processing to support live marketplace intelligence
• Ensure data reliability, governance, and accessibility across the organization
• Partner with engineering to embed intelligence directly into product workflows
• Work closely with the Head of Marketplace and engineering team to integrate AI capabilities into user-facing features
• Improve recommendation engines for suppliers and buyers on the platform
• Develop automated targeting systems for supply distribution and demand discovery
• Build intelligent alerts and opportunity detection systems
• Enable leadership with real-time dashboards and predictive analytics
• Build internal tools that surface emerging supply shortages, price movements, and liquidity gaps
• Create experimentation frameworks for marketplace optimization
• Support company-wide data-driven decision making
• Design systems that scale with Matium’s expansion into multiple raw material markets
• Ensure models improve with increased transaction volume and network density
• Establish data science and machine learning best practices across the organization

Requirements:

• 6+ years of experience in data engineering, machine learning, or applied AI
• Strong proficiency in Python, SQL, and modern data stack technologies
• Experience building and deploying machine learning models in production environments
• Familiarity with distributed data systems and cloud infrastructure
• Experience designing scalable data pipelines and analytics architectures
• Strong problem-solving mindset and systems thinking
• Comfort operating in fast-moving startup environments
• Experience with recommendation systems, marketplace algorithms, or predictive modeling