Senior AI Research Engineer
At a glance
Senior AI Research role at Zero RFI. San Francisco · full-time · $250,000–$300,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Develop generative models for floor plans, facades and structural design, with building constraints in mind
- Create vision systems that inspect design drawings and recover three-dimensional building forms
- Use graph learning and reinforcement learning to improve structural, MEP and building-performance outcomes
- Connect AI models to BIM software, then deploy them with tracking, version control and A/B testing
- Work with architects and engineers on buildable designs, and lead research projects that share findings
What you bring
- A relevant master's or PhD, or equivalent experience in the field
- At least three years building and deploying machine-learning models in production
- A strong grounding in deep learning, computer vision, three-dimensional geometry and spatial reasoning
- Practical experience with generative models and Python scientific-computing libraries
- Experience with cloud ML services, distributed training, optimization and production software practices
Who this fits
This senior role suits an AI engineer focused on automated building design and research, with close collaboration alongside architects and engineers. The role is hybrid in San Francisco; Atlanta is also listed as a work location. Base salary is $250,000-$300,000, plus equity.
From the employer
Artificial intelligence is rewriting every industry it touches — but construction, the second largest sector in the global economy, has barely felt it yet. That's not a problem. That's an opening. 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. This isn't AI as a feature. It's AI as the foundation.
We are seeking a Senior AI Engineer to lead the development of automated building design systems and advance the state-of-the-art in AI/ML applications for the built environment. You'll architect and implement generative design algorithms, computer vision systems, and optimization models that fundamentally transform how buildings are conceived, designed, and validated. This role sits at the intersection of deep learning, computational geometry, and architectural design, creating AI systems that augment human creativity while respecting engineering constraints and building codes.
This is a rare opportunity to apply cutting-edge AI research to one of humanity's most fundamental challenges: creating better spaces for people to live, work, and thrive.
Key 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).
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).
Integrate AI models with industry-standard BIM tools (Revit, Rhino/Grasshopper) through custom APIs and plugins.
Deploy production ML pipelines using modern MLOps practices, including experiment tracking (Weights & Biases, MLflow), model versioning, and A/B testing frameworks.
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.
Requirements
Master's degree or PhD in Computer Science, AI/ML, Computational Design, or related field (or equivalent industry experience).
3-5+ years of hands-on experience building and deploying ML models in production environments.
Deep expertise with modern deep learning frameworks (PyTorch preferred).
Strong foundation in computer vision, 3D geometry processing, and spatial reasoning algorithms.
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.
Understanding of optimization techniques (genetic algorithms, gradient-based optimization, constraint satisfaction).
Strong software engineering practices and experience with containerization (Docker) and orchestration (Kubernetes).
Excellent communication skills to translate complex AI concepts to domain experts and stakeholders.
Preferred Qualifications (A plus, not a requirement)
Experience with computational design tools (Grasshopper, Dynamo) and parametric modeling.
Familiarity with building information modeling (BIM) standards and IFC data schemas.
Knowledge of graph neural networks (PyTorch Geometric, DGL) for structural and spatial analysis.
Experience with physics simulation engines (Mujoco, Isaac Sim) or FEA integration.
Background in multi-agent reinforcement learning for complex system optimization.
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).
Understanding of construction workflows and building codes.
What We Offer
Compensation that reflects the role: Base salary $250,000–$300,000 plus meaningful early-stage equity. You're not joining a company where the upside is already priced in — you're one of the people pricing it.
Hybrid work, your way: San Francisco or Atlanta, with a one-time home office stipend to build the setup you actually want.
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.
Tools without bureaucracy: A curated toolkit of AI, development, and research resources with the autonomy to use what works.
A network you can't buy: Direct exposure to ZeroRFI's owner and developer community — 53,000+ AEC industry subscribers, live events, and the relationships that matter in this industry.