Generative AI Engineer / Scientist (US)

Genia; Los Angeles (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Genia, based in Los Angeles, seeks a Generative AI Engineer/Scientist to advance next-generation AI systems that combine LLMs, agentic AI, graph neural networks, and image generation. You will design and fine-tune models for architecture and engineering applications, prototype multimodal systems, and collaborate with product and engineering teams to integrate AI into design workflows.

The role favors applicants with strong foundations in deep learning, PyTorch, and experience with LLMs, GNNs,

Qualifications

• Strong foundation in deep learning and generative AI models.

Responsibilities

• Design, fine-tune, and optimize LLMs for domain-specific applications in architecture and engineering.

Skills

LLMs

Agentic AI

GNNs

Python

PyTorch

Multimodal systems

Education

Bachelor's or higher in CS/AI

PhD preferred

Tools

PyTorch Geometric

DGL

Python

TensorFlow / JAX

Job description

Responsibilities

We are looking for a Generative AI Engineer / Scientist to help build next-generation AI systems that combine large language models (LLMs), agentic AI, graph neural networks (GNNs), and image generation algorithms. This role is an opportunity to work on real-world applications at the intersection of architecture, engineering, and AI, while shaping the future of generative design.

• Design, fine-tune, and optimize large language models (LLMs) for domain-specific applications in architecture and engineering.
• Develop agentic AI systems for reasoning, tool use, and workflow automation in structural design tasks.
• Apply graph neural networks (GNNs) to structured engineering data, knowledge graphs, and design optimization problems.
• Prototype multimodal systems combining text, drawings, and structured design data.
• Collaborate with product and engineering teams to integrate generative AI into production-ready AEC workflows.
• Stay on top of the latest AI research and propose innovative solutions to push the boundaries of generative design.

Qualifications

EDUCATION & BACKGROUND

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong academic/industrial foundation in deep learning and generative AI models, geometric learning and computational geometry.

CORE EXPERTISE

• Hands-on experience with LLMs: fine-tuning, instruction tuning, domain adaptation, or RLHF.
• Experience developing agentic systems (e.g., tool-augmented LLMs, reasoning frameworks).
• Strong knowledge of graph neural networks (GNNs) using PyTorch Geometric, DGL, or similar.
• Skilled in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).
• Able to navigate ambiguity and adapt effectively to evolving requirements in fast-paced environments.

Preferred Qualities

• Track record of publications in top AI/ML/NLP/CV conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD).
• Contributions to open-source AI projects or a demonstrable portfolio of generative AI applications.
• Experience working with multimodal or AEC-related datasets is a strong plus.
• Excited by working in a fast-growing startup environment and contributing to both research and product impact.