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Principal Data Scientist – Gen AI

Job in Silver Spring, Montgomery County, Maryland, 20900, USA
Listing for: Jobtailor
Full Time position
Listed on 2026-07-13
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 150000 - 210000 USD Yearly USD 150000.00 210000.00 YEAR
Job Description & How to Apply Below

Responsibilities

  • Own and drive an 18-24 month technical roadmap that balances innovation with disciplined business value delivery.
  • Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing.
  • Provide technical leadership to the Generative AI team, setting technical direction and defining best practices.
  • Influence the roadmaps, priorities, and resourcing of partner engineering, product, and business teams.
  • 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.
  • Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models.
  • Serve as a respected subject matter expert and mentor to scientists and engineers across the organization.
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.
  • A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
  • 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, Tensor Flow, 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.
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