Principal Data Scientist - Gen AI

Xometry is seeking an exceptional Principal Data 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 role will also serve as a key technical leader for high-stakes strategic initiatives, including the DFM AI + IQE integration with Siemens.

Responsibilities

Own and drive an 18-24 month technical roadmap that balances innovation with disciplined business value delivery; Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them 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; Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models; Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development; Champion the adoption of better approaches across teams and functions; Influence the roadmaps, priorities, and resourcing of partner engineering, product, and business teams; Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications; Serve as the technical architect for the embedded DFM AI + IQE track, leading the integration of Xometry's proprietary AI directly into the Siemens ecosystem, including Designcenter and Teamcenter; Operate directly on native 3D geometry to enable real-time manufacturability feedback and pricing; Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models; Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment; Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency; Serve as a respected subject matter expert and mentor to scientists and engineers across the organization; Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies; Stay updated with the latest research in generative AI, deep learning, and multimodal data processing

Requirements

Typically 10-plus years of experience with a broad and deep portfolio of applied ML and data science work, or a PhD with 6-plus years of relevant experience; Bachelor's degree required; Expert-level proficiency in Python and advanced scientific computing, with a track record of building large-scale, production-grade ML systems; Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy; Recognized depth in machine learning and statistical methodology; Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs) and experience with multimodal data processing (e.g., combining text, image, and 3D data); Strong background in probability, statistics, and optimization techniques relevant to generative modeling; Demonstrated ability to drive 18-24 month technical initiatives that deliver lasting organizational and business impact; Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker); Familiarity with software engineering principles, including version control, reproducibility, and continuous integration; Exceptional influence and communication skills, with a track record of aligning executives and cross-functional partners around ambitious scientific directions

Nice to have

Advanced degree (M.S. or PhD) in computer science, machine learning, AI, or related field; Experience in manufacturing, supply chain, or similar industries

Benefits

Competitive benefits package; 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; bonus