AI/ML Researcher – Intermediate/Senior

Hedral

Machine Learning Scientist developing AI-driven design systems for architectural and engineering projects. Building models that reason over complex data using machine learning and spatial reasoning.

Posted 6/24/2026full-timeAustin • New York, Texas • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design and develop machine learning models for understanding and reasoning over architectural plans, engineering documents, and spatial data.
Build and deploy systems using vision, language, and graph-based models to process 2D drawings, 3D geometries, and structured engineering data.
Develop and train surrogate models for structural and MEP simulations to accelerate design evaluation.
Design and implement reinforcement learning and optimization systems for automated and combinatorial design problems.
Build robust data pipelines and training infrastructure for large-scale, domain-specific datasets.
Collaborate closely with engineering and product teams to integrate ML models into production workflows.
Lead experimentation, evaluate model performance on real-world use cases, and iterate rapidly to improve system quality and reliability.
Contribute to the overall system design, including modeling decisions, architecture choices, and scaling strategies.

Requirements

What you’ll need

Master's degree in Machine Learning, Computer Science, Engineering, Applied Mathematics, or a related field; PhD is preferred but not required.
3+ years of industry or equivalent research experience building and deploying ML systems.
Proficiency in Python and deep learning frameworks such as PyTorch (preferred), JAX, and TensorFlow.
Strong understanding of modern ML techniques, including deep learning, reinforcement learning, and model evaluation.
Experience designing and implementing end-to-end ML systems, from data processing to model deployment.
Strong publication record with the ability to build on recent ML literature, ship production-ready systems, and operate independently in ambiguous environments.

Benefits

Comp & perks

Competitive Compensation and Benefits
Environment for growth
Hybrid and flexible work environment
Opportunity to work on high-impact, real-world problems at the intersection of AI and engineering
A fast-paced environment with significant technical ownership and growth

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningreinforcement learningdeep learningmodel evaluationdata processingmodel deploymentsurrogate modelsoptimization systemsdata pipelinesarchitectural plans

Soft Skills

collaborationleadershipexperimentationproblem-solvingindependencecommunicationiterationevaluationdesign decision-makingscaling strategies

Certifications

Master's degree in Machine LearningMaster's degree in Computer ScienceMaster's degree in EngineeringMaster's degree in Applied MathematicsPhD in related field