Generative AI Engineer / Scientist

Role Overview

We are seeking a Generative AI Engineer / Scientist to contribute to pioneering AI systems that integrate large language models (LLMs), agentic AI, graph neural networks (GNNs), and image generation technologies. This position offers a chance to work on impactful solutions at the crossroads of architecture, engineering, and artificial intelligence, influencing the future landscape of generative design.

Key Responsibilities

• Architect, fine-tune, and enhance large language models tailored for specialized applications within architecture and engineering domains.
• Create agentic AI frameworks for reasoning, tool integration, and automating workflows related to structural design.
• Implement graph neural networks for processing structured engineering datasets, knowledge graphs, and optimization in design tasks.
• Develop prototypes for multimodal systems that integrate text, visual drawings, and structured design data.
• Collaborate closely with product development and engineering teams to embed generative AI capabilities into scalable Architecture, Engineering, and Construction (AEC) workflows.
• Continuously monitor advancements in AI research and propose innovative approaches to advance generative design technologies.

Candidate Qualifications

• Educational background with a Bachelor's, Master's, or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related disciplines.
• Robust academic or industry experience in deep learning, generative AI models, geometric learning, and computational geometry.

Core Competencies

• Proficient in working with large language models, including fine-tuning, instruction tuning, domain adaptation, or reinforcement learning with human feedback (RLHF).
• Experience in designing agentic AI systems such as tool-augmented LLMs and reasoning frameworks.
• Deep understanding of graph neural networks, utilizing libraries like PyTorch Geometric, DGL, or equivalents.
• Strong programming skills in Python and expertise with deep learning libraries such as PyTorch, TensorFlow, or JAX.
• Ability to manage ambiguity and adapt efficiently to changing priorities in a dynamic, high-growth startup environment.

Preferred Attributes

• Published research in prestigious AI, machine learning, NLP, or computer vision conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD).
• Active contributions to open-source projects related to AI or a portfolio showcasing generative AI applications.
• Experience handling multimodal or datasets related to AEC domains is highly advantageous.
• Motivated to work in an entrepreneurial setting, contributing significantly to both academic research and product development.

Additional Information

Applicants should submit their resume accompanied by a short summary of their background in residential construction sales via email to hr [at] genia.design.

We eagerly anticipate collaborating with new talent passionate about shaping the future of generative design.