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 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 an 18-24 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.

*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 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 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 Designcenter and Teamcenter.
• 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., AWS) for large-scale data processing, model training, and deployment. Continuously experiment and iterate on model performance, tuning architectures and parameters.
• 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.

What You'll Bring to Xometry

• Experience & Education: Typically 10+ years of experience with a broad and deep portfolio of applied ML and data science work; or a PhD with 6+ years of relevant experience. A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Technical Mastery: Expert-level proficiency in Python and advanced scientific computing, with a track record of building large-scale, production-grade ML systems. Proficient in Python, including key 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 (e.g., Transformers, GPT, VLMs) and experience with multimodal data processing. Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Strategic & Operational Skills: Demonstrated ability to drive 18-24 month technical initiatives that deliver lasting organizational and business impact. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker), and familiar with software engineering principles including version control, reproducibility, and continuous integration.
• Communication: Exceptional influence and communication skills, with a track record of aligning executives and cross-functional partners around ambitious scientific directions.
• Domain Expertise (Plus): Experience in the manufacturing, supply chain, or similar industries is a plus.