Principal Data Scientist - Gen AI

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Xometry is seeking an exceptional Principal Data Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine‑tuning generative and language models, multimodal document understanding, and structured data extraction. This role will also serve as a key technical leader for high‑stakes strategic initiatives, including the DFM AI + IQE integration with Siemens.

In this role, you will serve as a technical leader, owning a 12‑month technical roadmap, driving large‑scale cross‑functional ML and AI initiatives, and setting the long‑term scientific direction for AI‑driven solutions that enhance Xometry's service offerings.

This role requires a hybrid schedule (3 days a week) at our Waltham, MA or North Bethesda, MD office location.

• Technical Vision and
  
  Roadmap:
  
  Own and drive an 18‑24 month technical roadmap that balances innovation with disciplined business value delivery. Lead strategic planning and roadmap development for generative AI initiatives, identifying high‑impact projects and aligning them with Xometry's business objectives.
• Generative AI Development: Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image‑based data processing solutions, including training and fine‑tuning generative and language models.
• Technical Leadership & Standards: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. Champion the adoption of better approaches across teams and functions.
• Cross‑Functional Leadership: Influence the roadmaps, priorities, and resourcing of partner engineering, product, and business teams. Collaborate with cross‑functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications.
• Siemens Partnership Integration (DFM/IQE): Serve as the technical architect for the embedded DFM AI + IQE track, leading the integration of Xometry's proprietary AI directly into the Siemens ecosystem, including Design center and Teamcenter. This work involves operating directly on native 3D geometry to enable real‑time manufacturability feedback and pricing, creating a 'science fiction speed' digital thread from ideation to delivery.
• Data & ML Operations: Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. Utilize cloud platforms (e.g., Amazon Web Services) for large‑scale data processing, model training, and deployment. Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast‑paced, agile environment.
• Organizational Development: Serve as a respected subject matter expert and mentor to scientists and engineers across the organization. Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem‑solving strategies to elevate the team's technical capabilities. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing.

• Experience &
  
  Education:
  
  Typically 10-plus years of experience with a broad and deep portfolio of applied ML and data science work; or a PhD with 6-plus years of relevant experience. A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI,…