neoBIM is a well-funded start-up software company revolutionizing the way architects design buildings with our innovative BIM (Building Information Modelling) software. As we continue to grow, we are building a small and talented team of developers to drive our software forward.

We are looking for a highly skilled Generative AI Developer to join our AI team. The ideal candidate should have strong expertise in deep learning, large language models (LLMs), multimodal AI, and generative models (GANs, VAEs, Diffusion Models, or similar techniques).

This role offers the opportunity to work on cutting-edge AI solutions, from training models to deploying AI-driven applications that redefine automation and intelligence.

• Develop, fine-tune, and optimize Generative AI models, including LLMs, GANs, VAEs, Diffusion Models, and Transformer-based architectures.
• Work with large-scale datasets and design self-supervised or semi-supervised learning pipelines.
• Implement multimodal AI systems that combine text, images, audio, and structured data.
• Optimize AI model inference for real-time applications and large-scale deployment.
• Build AI-driven applications for BIM (Building Information Modeling), content generation, and automation.
• Collaborate with data scientists, software engineers, and domain experts to integrate AI into production.
• Stay ahead of AI research trends and incorporate state-of-the-art methodologies.
• Deploy models using cloud-based ML pipelines (AWS/GCP/Azure) and edge computing solutions.

Must-Have Skills

• Strong programming skills in Python (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, including Diffusion Models (e.g., Stable Diffusion, DALL-E, Imagen), GANs, VAEs.
• Hands-on experience with transformer-based architectures (e.g., Vision Transformers, BERT, T5, GPT, etc.).
• Experience with MLOps frameworks for scaling AI applications (Docker, Kubernetes, MLflow, etc.).
• 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 NeRFs (Neural Radiance Fields) for 3D generative AI.
• Knowledge of AI for Architecture, Engineering, and Construction (AEC).
• Understanding of distributed computing (Ray, Spark, or Tensor Processing Units).
• Familiarity with AI model compression and inference optimization (ONNX, TensorRT, quantization techniques).
• Experience in cloud-based AI development (AWS/GCP/Azure).

• Work on high-impact AI projects at the cutting edge of Generative AI.
• Competitive salary with growth opportunities.
• Access to high-end computing resources for AI training & development.
• A collaborative, research-driven culture focused on innovation & real-world impact.
• Flexible work environment with remote options.