Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Benefits
- Meaningful early-stage equity participation
- Full benefits package
Company Overview