Staff Machine Learning Engineer - Generative 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 a Staff Machine Learning Engineer to lead our Generative AI efforts. This is a rare opportunity to shape the future of manufacturing by applying cutting-edge AI research to real-world problems: from multimodal document understanding, to extracting structured data from technical drawings, to building new ways of reasoning across text, images, and 3D data. If you’re passionate about building state-of-the-art AI systems and want to see your work have immediate business and customer impact, we’d love to talk.

How You’ll Contribute:

• Lead with vision – Set the technical direction for our Generative AI team, establish best practices, and inspire high-impact innovation


• Drive strategy – Help shape the AI roadmap, identifying the most valuable opportunities to apply generative AI across Xometry’s marketplace


• Build cutting-edge models – Develop and deploy large language and generative models for multimodal document processing and structured data extraction


• Innovate across modalities – Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions


• Engineer at scale – Create data pipelines and training workflows that can handle massive, complex datasets


• Deploy in the cloud – Use AWS and other platforms to train, optimize, and deploy models into production at scale


• Collaborate widely – Work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows


• Mentor and grow – Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team


• Stay ahead – Keep up with the latest generative AI and deep learning research, and bring fresh ideas into production

What You'll Bring to Xometry:

• Bachelor’s degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or related field is a big plus


• 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision


• Strong track record working with large-scale language and vision models (Transformers, GPT, VLMs)


• Hands-on experience with multimodal data (text, images, 3D)


• Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy)


• Solid grounding in probability, statistics, and optimization for generative modeling


• Experience deploying ML and AI models using cloud microservice architecture (AWS preferred)


• Strong software engineering skills, including object oriented programming, testing, version control, CI/CD best practices and IaC (terraform preferred)


• A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders


• Background in manufacturing, supply chain, or related industries is a plus — but curiosity and drive matter more


• Must be a U.S. Citizen or Green Card holder (ITAR compliance)

We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention 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 that you are authorized to work in the U.S.