2 months ago
Responsibilities
- Lead multiple large, cross-functional ML/AI solutions with significant and lasting business impact.
- Define and drive an 18- to 24-month ML/AI technical roadmap balancing innovation with reliable business value.
- Influence engineering, product, operations, manufacturing, design, and business roadmaps, priorities, and resourcing.
- Identify and remove technical, operational, data, and resource roadblocks across teams and projects.
- Mentor ML engineers, data scientists, AI researchers, and technical teams.
- Guide ML/AI infrastructure, data, model, tooling, governance, and operationalization decisions as a subject-matter expert.
- Identify and lead ML/AI opportunities involving revenue growth, cost reduction, quality inspection, quoting, 3D classification, and manufacturing-ready model generation.
- Monitor industry developments in ML, AI, generative AI, 2D/3D modeling, and manufacturing technology and translate them into internal practices.
- Improve inference latency, model retraining intervals, feature pipelines, compute costs, and manual-task automation.
Requirements
- Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or a related field; a PhD is preferred for deep generative or 3D modeling work.
- 12+ years of professional experience in machine learning, artificial intelligence, or data science, including several years leading major programs in a senior or principal capacity.
- Experience architecting and delivering large-scale ML/AI solutions end to end, from data ingestion and feature engineering through training, evaluation, deployment, monitoring, and operations.
- Deep expertise with TensorFlow, PyTorch, data engineering, model infrastructure, MLOps, cloud platforms, and scalable production systems.
- Experience with 3D modeling, geometry, computer vision, generative models, point-cloud processing, mesh processing, text-to-3D, image-to-3D, or CAD/CAM integration is highly desirable.
- Strong exposure to generative AI techniques including large language models, multimodal models, diffusion, and GANs, with experience translating them into business use cases.
- Ability to collaborate across product, engineering, operations, manufacturing, design, and business leadership and explain technical concepts in business terms.
- Proven ability to influence without direct authority, drive organizational change, communicate technical vision and trade-offs, and deliver measurable business impact.
- Experience mentoring and guiding ML engineering, data science, or AI research teams and shaping their practices, culture, and career growth.
Benefits
- Competitive benefits package including a 401(k) match, medical, dental, and vision insurance.
- Life and disability insurance, generous paid time off, vacation, sick leave, floating and fixed holidays, maternity and bonding leave, EAP, and other wellbeing resources.
- Hybrid work arrangement, indicated by the #LI-Hybrid designation.
Tech Stack
Categories
About Xometry
Xometry builds an AI-enabled marketplace that connects engineers and procurement teams with a vetted global network of manufacturers for on-demand CNC machining, 3D printing, sheet metal, and injection molding. The company earns fees by brokering instant-quote RFQs and managing production, logistics, and quality across its supplier base. Founded in 2013, Xometry is a publicly traded company (NASDAQ: XMTR) based in the Washington, DC–Baltimore area and serves buyers from startups to Fortune 1000 firms.