Senior Data Scientist

5 days ago

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Xometry

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Direct Metal Laser Sintering (DMLS) • CNC Machining • Production Manufacturing • Rapid Prototyping • 3D Printing

1001 - 5000

💰 $75M Series E on 2020-09

Description

• 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 model architectures, continuously optimizing VLM performance in a fast-paced, iterative environment. • Work within a team-oriented setting, participating in peer reviews, sharing insights, and contributing to an environment of continuous learning and improvement.

Requirements

• A bachelor’s degree is required; an advanced degree (M.S. or PhD) in computer science, data science, machine learning, or a related field is highly preferred. • 5+ years of experience in data science and machine learning, with expertise in Visual Language Models or multimodal machine learning. • Strong experience with machine learning libraries and frameworks such as PyTorch, TensorFlow, or Hugging Face. • Proficiency in Python, including libraries like pandas, numpy, and scikit-learn. • Solid understanding of deep learning techniques and experience with transfer learning, fine-tuning, and model evaluation. • Experience with cloud platforms (e.g., AWS SageMaker) for model training and deployment. • Familiarity with data processing and visualization tools (SQL, Jupyter Notebooks, Looker, etc.) and basic database knowledge (e.g., Snowflake, MongoDB). • Excellent analytical and problem-solving skills, with a strong ability to work in an environment that values teamwork, innovation, and continuous learning. • Familiarity with computer vision tasks and frameworks, as well as experience with multimodal data, is a plus.