Staff Data Scientist

Role Overview

Xometry is looking for a technically deep and strategically minded Staff Data Scientist to lead a high-stakes partnership with a major enterprise partner. In this role, you will be the technical architect behind the embedded DFM AI + IQE track, moving beyond simple plug-ins to integrate Xometry’s proprietary AI directly into our partner's ecosystem.

You will lead the extraction and embedding of our core AI engines—focused on Design for Manufacturability (DFM) and Instant Quoting (IQE)—directly into the partner's core software and product lifecycle management (PLM) platforms, operating directly on native 3D geometry.

How You'll Contribute

• Technical Leadership & Partner Integration: Lead the design and delivery of production ML solutions embedding AI into ecosystem workflows, transitioning vertically integrated services to SaaS solutions.
• Cross-Functional Strategy: Partner with external technical leads and internal leadership to align science priorities, influencing handling of native 3D geometry vs. mesh-based formats.
• Roadmap Ownership: Define and own the 12-month science roadmap, bridging DFM & Pricing integration with Full Part Lifecycle & Marketplace integration.
• Risk Management & Execution: Anticipate technical hurdles in ring-fenced data environments and enterprise-grade deployments.
• Mentorship and Standards: Provide technical guidance to scientists, driving adoption of shared frameworks and reusable tooling.

Qualifications

• Minimum of 8 years in data science/ML with a Bachelor's; 5-6+ years with a Master's; or a PhD with 3-4+ years of applied experience.
• Expert-level proficiency in Python and SQL.
• Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred.
• Proven ability to lead cross-functional delivery for high-value external partnerships.
• Track record of executing long-term science roadmaps translating manufacturing physics into real-time pricing and DFM outcomes.
• Strong communication skills to translate complex technical trade-offs.

Preferred Experience

• Experience in CAD/PLM software, computational geometry, or industrial manufacturing.
• Experience shipping production-grade ML models handling massive, multi-modal datasets.
• Experience shaping ML infrastructure for ring-fenced/dedicated tenant environments.
• Background in dynamic pricing, supply chain optimization, or high-volume marketplace modeling.