Principal Machine Learning Data Scientist, Gen AI

Position Overview

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting 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 a Principal Data & ML 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 person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings.

Xometry is an equal opportunity employer. All applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles, Xometry participates in E-Verify and, after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm your authorization to work in the U.S.

Key Responsibilities

• Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring adherence to industry standards in AI and ML development.
• Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects aligned with Xometry's business objectives.
• 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.
• Drive the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models.
• Design and implement efficient workflows for data preparation, cleaning, and augmentation to support model training.
• Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment.
• Collaborate with cross-functional teams, including engineering and business units, to ensure that generative AI solutions meet business needs.
• Mentor team members on advanced machine learning techniques, model architecture design, and problem-solving strategies.
• Continuously experiment with and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment.
• Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, and incorporate best practices into model development.

Required Qualifications

• Bachelor's degree is required; an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• 7+ years of experience in data science and machine learning, with a focus on generative models, large language models, or computer vision.
• Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs).
• Experience with multimodal data processing (combining text, image, and 3D data).
• Proficient in Python and key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Knowledge of software engineering principles, including version control, reproducibility, and continuous integration.

Preferred Qualifications

• Experience in the manufacturing, supply chain, or similar industries is a plus.