Autodesk

Principal Research Engineer – AEC Geometric Data, Generative AI

Autodesk

full-time

Posted on:

Origin:  • 🇺🇸 United States • California, Massachusetts, North Carolina

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Salary

💰 $146,900 - $237,600 per year

Job Level

Lead

Tech Stack

AWSCloudPythonPyTorch

About the role

  • Lead and collaborate with other engineers to develop scalable data pipelines for diverse AEC data sources
  • Mentor junior engineers and provide technical guidance on complex data engineering challenges
  • Work with large-scale, multi-modal datasets including text and geometric data, to support preprocessing, augmentation, analysis and content understanding
  • Transform unstructured AEC data into representations suitable for machine learning
  • Lead cross-functional collaboration with ML Research Scientists and Engineers to align data formats with downstream training and fine-tuning of LLMs
  • Apply deduplication, normalization, and validation techniques to ensure high-quality data at scale
  • Architect and optimize pipelines for scalability, reproducibility, and cloud deployment
  • Drive technical decision-making and influence engineering best practices across the team
  • Perform requirements analysis, working with team members of different levels and documenting solutions clearly
  • Lead initiatives to communicate findings through quantitative analysis, visuals, and clear insights
  • Contribute to agile workflows, ensuring flexibility and responsiveness to evolving project needs
  • Participate in technical planning and roadmap development

Requirements

  • MSc in Computer Science, Engineering, or a related field
  • 7-10+ years of experience in Machine Learning , Engineering, or related fields
  • 2+ years of experience leading technical projects or mentoring junior engineers
  • Demonstrated ability to provide technical leadership in cross-functional environments
  • Hands-on experience in data modeling, architecture, and processing across multiple representations, including 2D/ 3D geometry
  • Experience with computational geometry and geometric data methods
  • Familiarity with machine learning concepts and frameworks and how data is represented for training
  • Proficiency in Python and strong software engineering practices
  • Ability to translate theoretical concepts into practical solutions and prototypes
  • Strong documentation skills for code, architectures, and experiments
  • Background in Architecture, Engineering, or Construction (AEC)
  • Excellent communication skills with ability to influence and guide technical decisions
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