Generative 3D AI Developer for BIM

Role Overview: You will be joining the AI team of neoBIM, a well-funded start-up software company that is revolutionizing the architecture industry with innovative BIM software. As a Generative AI Developer, you will play a key role in developing cutting-edge AI solutions, optimizing Generative AI models, and building AI-driven applications for automation and intelligence. Key Responsibilities: - Develop, fine-tune, and optimize Generative AI models such as LLMs, GANs, VAEs, Diffusion Models, and Transformer-based architectures. - Work with large-scale datasets to design self-supervised or semi-supervised learning pipelines. - Implement multimodal AI systems that integrate text, images, audio, and structured data. - Optimize AI model inference for real-time applications and large-scale deployment. - Collaborate with cross-functional teams to integrate AI into production and build AI-driven applications for BIM, content generation, and automation. - Stay updated on AI research trends and incorporate state-of-the-art methodologies. - Deploy models using cloud-based ML pipelines and edge computing solutions. Qualifications Required: Must-Have Skills: - Strong programming skills in Python using PyTorch, TensorFlow, JAX, or equivalent. - Experience in training and fine-tuning Large Language Models (LLMs) like GPT, BERT, LLaMA, or Mixtral. - Expertise in Generative AI techniques such as Diffusion Models, GANs, VAEs, and transformer-based architectures. - Hands-on experience with MLOps frameworks for scaling AI applications like Docker, Kubernetes, and MLflow. - Proficiency in data preprocessing, feature engineering, and AI pipeline development. - Strong background in mathematics, statistics, and optimization related to deep learning. Good-to-Have Skills: - Experience in Neural Radiance Fields (NeRFs) for 3D generative AI. - Knowledge of AI for Architecture, Engineering, and Construction (AEC). - Understanding of distributed computing using Ray, Spark, or Tensor Processing Units. - Familiarity with AI model compression and inference optimization techniques like ONNX, TensorRT, and quantization. - Experience in cloud-based AI development using AWS, GCP, or Azure. Please omit the "Benefits" section as it is not relevant to the job description.,