Senior Data Scientist, LLM

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 13, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Senior From the posting source

Schedule

Shift type

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Weekend work

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Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Data Scientist, LLM Buenos Aires, Argentina Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is seeking a Senior Data Scientist to join our Generative AI team. The candidate will focus on training and fine-tuning Visual Language Models (VLMs) for multimodal document understanding. The ideal candidate will leverage their expertise in machine learning and computer vision to advance Xometry's capabilities in processing and extracting structured data from complex documents and images. This is a 1-year contract. Responsibilities: Develop, fine-tune, and evaluate Visual Language Models (VLMs) to enhance document understanding, focusing on multimodal data such as text, images, and technical drawings. Design and implement data preparation, cleaning, and augmentation processes tailored to multimodal model training, ensuring high-quality data pipelines for VLMs. Leverage transfer learning and pre-trained models to accelerate model development and optimize performance on Xometry's specific data. Use cloud resources (e.g., Amazon Web Services) to scale training and fine-tuning processes for VLMs efficiently. Collaborate with data engineering and machine learning operations (MLOps) teams to deploy VLMs into production and monitor their performance. Interpret model outputs and improve model accuracy and robustness by applying data analysis and visualization tools (such as Python, Jupyter Notebooks, and SQL). Experiment with and implement state-of-the-art

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