Muir AI is building the Product Intelligence Platform – empowering companies to understand how their products are made, what they cost, and how they impact the environment. By combining AI with deep supply chain data, we give teams instant visibility into product cost drivers and carbon footprint, enabling faster, smarter decisions.

We’re looking for an AI Engineer to help develop the core models that power the Muir platform. You’ll work across the full lifecycle of applied ML researching, prototyping, and productionizing models that drive real-world product and supply chain intelligence. As part of a small, high-impact team, you’ll have broad ownership and the opportunity to shape both our modeling architecture and future roadmap.

• Design and build machine learning models to support cost modeling, carbon estimation, and supply chain analysis
• Explore, prototype, and validate new model features to increase accuracy, coverage, and speed
• Deploy models to production and ensure performance at scale
• Work with product, sales, and customer teams to translate real-world use cases into modeling solutions
• Contribute to a growing model stack that blends techniques across AI, structured data, and emerging technologies

• 3+ years of experience building and deploying machine learning models in production
• Strong Python skills and familiarity with core ML libraries and frameworks
• Familiarity with a range of modeling techniques including structured ML, graph-based models, or language models
• Experience working across the full ML lifecycle, from data exploration to deployment
• Comfort with ambiguity and ownership in early-stage environments
• Strong communication skills and ability to collaborate cross-functionally
• Based in or willing to relocate to the Seattle area
• Experience in manufacturing, supply chain, procurement, or sustainability domains (not required, but a plus)
• Startup or small team experience where you’ve worn multiple hats (not required, but a plus)