Principal Data Scientist - Gen AI

About the Role

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 serves as a key technical leader for strategic initiatives, including the DFM AI + IQE integration with Siemens, owning a multi-year technical roadmap, and setting the scientific direction for AI-driven solutions.

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

How You'll Contribute

• Technical Vision and Roadmap: Own and drive an 18-24 month technical roadmap balancing innovation with business value delivery. Lead strategic planning and roadmap development for generative AI initiatives.
• 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 training and fine-tuning of generative and language models.
• Technical Leadership & Standards: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring adherence to industry standards.
• Cross-Functional Leadership: Influence roadmaps, priorities, and resourcing of partner engineering, product, and business teams.
• Siemens Partnership Integration (DFM/IQE): Serve as technical architect for the embedded DFM AI + IQE track, leading the integration of proprietary AI directly into the Siemens ecosystem (including Designcenter and Teamcenter) operating on native 3D geometry.
• Data & ML Operations: Design and implement efficient workflows for data preparation, cleaning, and augmentation. Utilize cloud platforms (e.g., AWS) for large-scale data processing, model training, and deployment in an agile environment.
• Organizational Development: Serve as a subject matter expert and mentor to scientists and engineers across the organization. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing.

Qualifications

• Experience & Education: Typically 10+ years of applied ML and data science experience, or a PhD with 6+ years of relevant experience. Bachelor’s degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or a related field highly preferred.
• Technical Mastery: Expert-level proficiency in Python and advanced scientific computing with libraries such as PyTorch, TensorFlow, pandas, and numpy.
• AI/ML Expertise: Recognized depth in machine learning and statistical methodology. Expertise in large-scale language and vision models (Transformers, GPT, VLMs) and multimodal data processing (combining text, image, and 3D data).
• Engineering & Cloud Skills: Familiarity with cloud resources for model training and deployment (e.g., AWS SageMaker) and software engineering principles (version control, reproducibility, continuous integration).
• Communication: Exceptional influence and communication skills with a track record of executive and partner alignment.
• Domain Expertise (Plus): Experience in manufacturing, supply chain, or similar industries is a plus.