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Principal Machine Learning Data Scientist - Generative AI

XometryWaltham, MA
On-site Full-time $164K/yr - $213K/yr

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Experience Level

Senior

Qualifications

Key Responsibilities:Provide technical leadership to the Generative AI team, establishing technical direction, defining best practices, and ensuring adherence to industry standards in AI and ML development. Spearhead strategic planning and roadmap development for generative AI projects, identifying high-impact initiatives in alignment with Xometry’s business goals. Design and implement generative AI models and large language models (LLMs) for multimodal document processing, focusing on the extraction of structured data from technical drawings, purchase orders, and other complex documentation. Lead the innovation and development of novel text and image-based data processing solutions, including training and fine-tuning generative and language models.

About the job

Xometry (NASDAQ: XMTR) is at the forefront of innovation, bridging the gap between visionary thinkers and the manufacturers who actualize their ideas. Our cutting-edge digital marketplace equips manufacturers with vital resources to scale their businesses while enabling Fortune 1000 companies to seamlessly access global manufacturing capabilities.

We are on the lookout for a Principal Data & ML Scientist to join our Generative AI team. The perfect candidate will be enthusiastic about driving advancements in machine learning and generative AI, especially in fine-tuning generative and language models, multimodal document comprehension, and structured data extraction. You will utilize your deep knowledge of generative models and data science to create and refine innovative AI-driven solutions that elevate Xometry's service offerings.

About Xometry

Xometry is a pioneering leader in the manufacturing industry, empowering creativity and innovation through technology. Our platform connects diverse industries with manufacturers, facilitating the realization of transformative ideas while promoting growth and efficiency in the manufacturing sector.

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