AI Researcher

• Conduct research, design, and implement novel Generative AI systems using LLMs, vision-language models, and advanced agentic frameworks (e.g., LangChain, LlamaIndex).
• Develop and optimize cutting-edge algorithms and methodologies for LLM fine-tuning, retrieval-augmented generation (RAG) optimization, and advanced context engineering.
• Perform rigorous experimentation and evaluation of novel GenAI-powered solutions to push the boundaries of model efficiency, performance, and robustness.
• Collaborate closely with engineering teams to guide the technical translation of research prototypes into production-grade, high-impact AI products.
• Contribute to the long-term AI research direction for the company, staying at the forefront of emerging techniques and academic breakthroughs.
• Develop and implement computer vision algorithms that significantly enhance the performance and functionality of our product.

Qualifications

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related quantitative field (Mathematics, Physics, Electrical Engineering, Computational Biology, etc.).
• Minimum of 5+ years of combined experience in AI/ML research and development, with a deep focus on Generative AI, LLMs, and Deep Learning.

Required Skills

• A strong, demonstrable track record of research impact, including a history of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ACL) or significant open-source contributions/patents in AI/ML.
• Expertise in the theory and practical application of LLM fine-tuning, advanced RAG architectures, and complex agentic systems.
• Exceptional proficiency in Python and deep expertise with major ML/Deep Learning frameworks (PyTorch, TensorFlow, Hugging Face Transformers).
• Strong foundation in software engineering and algorithm development, with experience working with large datasets.
• Exceptional problem-solving, creative thinking, and analytical skills.

• Experience with multimodal AI (vision-language models, diffusion models).
• Familiarity with the challenges and real-time considerations for managing AI workloads in a production environment.
• Knowledge of parallel computing and optimization techniques for large-scale model training and inference.

Why Join Us? Opportunity to define and shape the future of AI-powered solutions at the critical intersection of fundamental research and real-world product impact. Work directly on cutting-edge GenAI technologies with the potential for a significant global impact in the construction and design industry.

A collaborative, innovative startup environment with direct access to experienced founders. Flexible hybrid work arrangement.

If you are a pioneering researcher passionate about pushing the theoretical and practical boundaries of Generative AI, we would love to hear from you.

At Spacial, we’re redefining how the built world gets designed, engineered, and approved. With decades of combined experience across architecture, engineering, and construction, we’ve felt the industry’s pain points firsthand — slow approvals, endless redlines, and unclear requirements that derail even the best designs.

We built Spacial to fix that. Our AI-powered platform automates structural and MEP engineering, transforming 2D plans into permit-ready, code-compliant drawings in days, not months.

This isn’t just optimization. It’s a new standard built to give the AEC industry speed, clarity, and control from day one. By connecting architects, engineers, builders, and homeowners on a single platform, Spacial eliminates friction, streamlines approvals, and accelerates how ideas become reality.

About the Role: We are seeking a highly innovative AI Researcher to conduct fundamental and applied research, pioneering the next generation of Generative AI solutions. This role is focused on the theoretical and practical advancement of Large Language Models (LLMs), agent-based architectures, and novel algorithms to create transformative solutions for the construction and design industry. You will be responsible for conducting rigorous experimentation, contributing to the research roadmap, and translating groundbreaking research insights into real-world applications.