Staff Machine Learning Engineer - Generative AI

Reposted 4 Days Ago
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Lexington, KY, USA
In-Office
Senior level
Artificial Intelligence
The Role
Lead the Generative AI team by setting technical direction, developing large-scale models, and mentoring team members while collaborating across departments.
Summary Generated by Built In

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.

Responsibilities: 

  • 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.

Qualifications: 

  • 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)

#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.

Skills Required

  • Bachelor's degree in Computer Science, Machine Learning, AI, or related field
  • 5+ years of experience in machine learning or data science
  • Strong expertise in generative models, LLMs, or computer vision
  • Hands-on experience with multimodal data
  • Proficiency in Python and key ML libraries
  • Experience deploying ML and AI models using cloud microservice architecture
  • Strong software engineering skills including OOP, testing, version control, CI/CD
  • Must be a U.S. Citizen or Green Card holder

Xometry Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Xometry and has not been reviewed or approved by Xometry.

  • Healthcare Strength Core medical, dental, and vision coverage for employees and dependents is highlighted alongside mental‑health resources and an EAP. Feedback suggests many view the health plan as good or flexible, contributing positively to total rewards.
  • Retirement Support A 401(k) program and company‑paid life/STD/LTD are positioned as core financial protections. Feedback suggests retirement offerings are a consistent component of total compensation.
  • Leave & Time Off Breadth Flexible time off, paid holidays, volunteer time, and hybrid/remote options expand the time‑away and flexibility toolkit. Feedback suggests this breadth adds meaningful non‑cash value for many roles.

Xometry Insights

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The Company
Bethesda, MD
381 Employees
Year Founded: 2013

What We Do

Xometry is the leading AI-enabled marketplace for on-demand manufacturing, transforming one of the largest industries in the world. With its proprietary technology, Xometry creates a marketplace that enables designers and engineers to rapidly source high-quality on-demand manufactured parts and assemblies. Xometry's innovative platform also empowers sellers of manufacturing services across the nation to grow their businesses. Xometry’s buyers range from self-funded startups to Fortune 100 companies.

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