About Hedral

Hedral is establishing the new standard of building design, starting with structural engineering. Architecture and Structural Engineering are the art and science of crafting our environment — whether serving new builds or historic renovations, single-family homes or supertall skyscrapers. The product of their highly iterative collaboration is a prescription of how a project needs to be executed to the finest detail possible. Hedral’s mission is to isolate the science from the art in this process, reducing rote work and creating more rapid, data-driven feedback loops for design work using the latest technological innovations in generative design and AI. The result is a new breed of AEC firm that delivers the speed, reliability, and transparency that the industry severely needs.

Generative AI/Machine Learning Lead Software Engineer

As a Machine Learning Software Engineer you will be the member of the core team and will lead a team of technologists to build foundation models and generative AI tools for Hedral’s Platform. You will work collaboratively to experiment with and productize the use of machine learning and generative AI models in engineering software.

Responsibilities

• Lead the research of existing and upcoming Generative AI models and their applicability to AEC Software Design Tools

• Develop Prototypes to evaluate the productization of Machine Learning Models

• Evangelize and architect software product features to leverage the capabilities of Machine Learning and Generative AI for AEC Design

• Develop data collection / creation pipelines for training and/or fine tuning machine learning models

• Determine the productization readiness of research prototypes

• Collaborate with Frontend, Backend & Infrastructure in implementation of Gen AI & Machine Learning based data pipelines and features into the product.

Minimum Qualifications

• MS in Machine Learning, Applied Artificial Intelligence, Computer Science or related field.

• 5+ years of experience in machine learning, machine learning infrastructure and machine learning data infrastructure

• Domain expertise in training deep neural nets such as CNN and Transformers and developing production ML models

• Proficiency in at least one deep learning framework such as PyTorch, TensorFlow etc.

• Strong fundamentals in 3D Geometry, Geometric Computer Vision and Computational Geometry

• Good understanding of public cloud infrastructure with AWS

• Good understanding of fundamental CS algorithms and scaling behaviors of cloud native software

• Excellent ability to translate theoretical concepts into practical solutions and prototype implementations

Desired Qualifications

• Background in Architecture, Structural Engineering, CAE software

• Practical experience in data generation, data preparation and hyper-parameter selection

• Practical experience developing high scale machine learning algorithms

• Passionate about solving problems for AEC (Architecture, Engineering & Construction)

• Collaborative and comfortable assuming leadership roles with minimal direction

Remote restrictions

• Workday must overlap by at least 5 hours with Austin, TX, USA
• Must be a resident of United States