Senior Principal, ML/AI

Xometry is seeking a Senior Principal, Machine Learning & Artificial Intelligence to join our team. You will serve as a technical leader for large, cross-functional ML/AI initiatives that have significant and lasting business impact. You will own and drive an 18- to 24-month technical roadmap that balances innovation with business value delivery. You will work closely with engineering, product, design, manufacturing operations, and business leadership to influence partner roadmaps and resourcing. You will be a respected subject-matter expert, proactively removing roadblocks for teams and tackling problems beyond your immediate scope. You will identify and lead on opportunities to drive revenue growth, cost reduction, efficiency improvement, and competitive differentiation — especially in areas involving 2D/3D part understanding, generative AI, and advanced machine-learning platforms.

Responsibilities

• Serve as the technical leader of multiple large, cross-functional ML/AI solutions with significant, lasting impact across Xometry’s business.
• Define, and drive the 18-24-month ML/AI technical roadmap -  balancing breakthrough innovation (e.g., generative 3D, foundation models, large-scale vision/3D pipelines) with reliable business value delivery (e.g., quoting accuracy, lead-time reduction, defect detection, cost optimization)
• Influence partner roadmaps across engineering, product, operations, and business teams: align priorities, advise on resourcing, champion ML/AI best practices.
• Proactively identify and remove roadblocks for teams and projects — whether technical, operational, data-related, or resource constraints.
• Mentorship of individuals and technical teams
• Act as a trusted SME with strong cross-functional partnerships: your insights and guidance will shape ML/AI infrastructure, data, model, infrastructure, and tooling decisions.
• Play a leadership role in identifying areas of opportunity — e.g., using ML/AI to unlock new revenue streams (e.g., rapid quoting for new manufacturing modalities, generative design for customers), reduce cost (e.g., automated quality inspection), or optimize efficiency (e.g., 3D-geometry classification, defect detection, generating manufacturing ready models).
• Address problems adjacent to your sphere of immediate influence: proactively tackle challenges outside direct scope and champion holistic solutions.
• Stay ahead of industry developments in ML, AI, generative AI, 2D/3D modeling and manufacturing tech; translate insights into the improvement of internal best practices, tooling, frameworks, model governance, data pipelines, and operationalization.
• Consistently scrutinize existing work, identify opportunities for incremental growth and efficiency optimization - whether in inference latency, model retraining intervals, feature pipelines, cost of compute, or automation of manual tasks.

Qualifications

• Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering or related field (PhD preferred for deep generative/3D modeling emphasis).
• 12+ years of professional experience in machine learning, artificial intelligence, or data science roles — with several years in senior or principal capacity leading major programs.
• Demonstrated experience architecting and delivering large scale ML/AI solutions - end-to-end from data ingestion, feature engineering, model training, evaluation, deployment, monitoring & operations.
• Deep expertise in machine learning frameworks (TensorFlow, PyTorch), data engineering, model infrastructure, MLOps, cloud platforms (AWS, GCP, Azure), and scalable production systems.
• Experience in 3D modeling / geometry / computer vision / generative models (e.g., point-cloud processing, mesh processing, text23D, image23D, CAD/CAM integration) is highly desirable.
• Strong exposure to generative AI techniques (large language models, multimodal models, diffusion, GANs) and translating them into business use-cases.
• Excellent cross-functional collaboration skills: you can partner with product, engineering, ops, manufacturing, design, business leadership and translate technical concepts into business language.
• Proven ability to influence without direct authority and drive change across organizations.
• Strong communication and presentation skills; you can articulate technical vision, roadmap, trade-offs and outcomes to senior leadership.
• Track record of identifying and delivering measurable business impact via ML/AI - e.g., revenue growth, cost savings, improved efficiency.
• Experience mentoring and guiding teams of ML engineers / data scientists / AI researchers, shaping team culture, practices, and career growth.

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