Zero Emission Industries

Zero Emission Industries

Senior Research AI Engineer

San Francisco, CA · Senior

Sponsorship not specified$250k-$300kDetected 26 days ago
PythonAlgorithmsAWSAzureDockerKubernetesMachine LearningDeep LearningPyTorchscikit-learnNumPyNLPComputer VisionLLMsMLOpsA/B TestingDesign SystemsFEAStructural AnalysisResearchCommunicationRevitBIM

About the role

  • You're not joining a company where the upside is already priced in - you're one of the people pricing it.

Responsibilities

  • Design and implement generative AI models for automated building design, including floor plan generation, facade design, and structural optimization using state-of-the-art architectures (diffusion models, transformers, GANs).
  • Implement physics-informed neural networks for building performance simulation and predictive modeling.
  • Collaborate with architects and engineers to ensure AI systems produce practical, code-compliant, and constructible designs.
  • Lead research initiatives and publish findings to establish us as a thought leader in AEC AI innovation.
  • ZeroRFI is the AI company building the intelligence layer for the built environment - the platform that makes every building project smarter, faster, and more predictable than the last.
  • We're looking for a Principal Software Engineer to architect the systems that put AI at the center of how buildings get designed, built, and operated.

Requirements

  • Master's degree or PhD in Computer Science, AI/ML, Computational Design, or related field (or equivalent industry experience).
  • Experience with generative AI models (VAEs, GANs, Diffusion Models, Transformers) and their practical applications.
  • Proficiency in Python and scientific computing libraries (NumPy, SciPy, scikit-learn, Open3D, trimesh).
  • Experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML) and distributed training frameworks.
  • Strong software engineering practices and experience with containerization (Docker) and orchestration (Kubernetes).

Nice to have

  • Experience with computational design tools (Grasshopper, Dynamo) and parametric modeling.
  • Knowledge of graph neural networks (PyTorch Geometric, DGL) for structural and spatial analysis.
  • Experience with physics simulation engines (Mujoco, Isaac Sim) or FEA integration.
  • Contributions to open-source ML projects or published research in relevant venues (NeurIPS, ICML, CVPR, or domain-specific conferences).
  • Experience with point cloud processing and 3D scene understanding (PointNet++, DGCNN).

Skills

  • A curated toolkit of AI, development, and research resources with the autonomy to use what works.

Compensation

  • Compensation that reflects the role: Base salary $250,000–$300,000 plus meaningful early-stage equity.

Benefits

  • Compensation that reflects the role: Base salary $250,000-$300,000 plus meaningful early-stage equity.
  • Healthcare done right: Comprehensive coverage with multiple plan options - we're not making you figure it out yourself.
  • Unlimited PTO: We care about output, not hours logged.
  • Retirement options: Multiple investment vehicles to plan long-term.
  • Develop computer vision pipelines for design and drawing analysis using modern frameworks like YOLO, SAM, and NeRF-based 3D reconstruction.
  • Build graph neural networks and geometric deep learning models for structural analysis and MEP (Mechanical, Electrical, Plumbing) system optimization.
  • Create reinforcement learning systems for multi-objective building optimization (energy efficiency, cost, occupant comfort, sustainability metrics).
  • Hybrid work, your way: San Francisco or Atlanta, with a one-time home office stipend to build the setup you actually want.
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