We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Machine Learning / AI Engineer at HOMEKYND. . Location: US-Remote. Machine Learning / AI Engineer. . Homekynd is building the spatial intelligence layer for enterprise retail. Our platform transforms. . photos into 3D room models and powers immersive furniture visualization at scale, deployed in. . physical retail stores and embedded across enterprise ecommerce. We're a remote-first team. . on a fast build timeline, and we need engineers who want real ownership over hard problems.. . As Machine Learning / AI Engineer, you'll develop and integrate AI-driven features directly into. . the 3D visualization platform. Object placement, scene analysis, asset generation - you're. . applying machine learning to problems most engineers never get close to.. . What you'll do. . • Design, develop, and deploy ML models for object detection, scene understanding, and. . 3D asset placement. . • Train and fine-tune models on 3D datasets to generate realistic visualizations while. . preserving image fidelity. . • Collaborate with graphics and full-stack teams to integrate AI models into the product. . pipeline. . • Implement tools to automate image segmentation, furniture recognition, and style. . recommendations. . • Optimize model performance for real-time or near-real-time inference at scale. . • Stay current on generative AI and ML advancements and bring relevant capabilities into. . the platform. . What we're looking for. . • 3+ years in ML development with a focus on computer vision. . • Proficiency in Python and ML frameworks including PyTorch, TensorFlow, or Keras. . • Strong understanding of generative models (Stable Diffusion, GANs, VAEs) and LLM-. . based integrations. . • Experience with 3D data processing including point clouds, mesh recognition, and. . geometry analysis. . • Familiarity with object detection and segmentation tools (YOLO, Mask R-CNN). . • Ability to deploy models efficiently using TensorRT, ONNX, or serverless cloud. . deployments. . Bonus. . • Experience with ControlNet for AI-driven image conditioning. . • Familiarity with 3D file formats and workflows (glTF, OBJ). . • Experience with cloud-based ML platforms such as Vertex AI, AWS SageMaker, or. . Hugging Face. . • Background in recommendation systems for design suggestions or automated staging