We are seeking a highly skilled Data Scientist with strong expertise in Computer Vision and Generative AI to join our AI team. The ideal candidate will have hands\-on experience developing, fine\-tuning, and deploying state\-of\-the\-art vision and diffusion models for real\-world applications. You will work on advanced image understanding, segmentation, object detection, depth estimation, image generation, and image editing systems.
*Roles \& Responsibilities**
Design, train, fine\-tune, and deploy computer vision and generative AI models.
Develop solutions for object detection, segmentation, depth estimation, image inpainting, and virtual staging applications.
Build and optimize end\-to\-end pipelines for image understanding and image generation tasks.
Evaluate model performance using appropriate metrics and implement improvements.
Create and maintain data annotation, training, validation, and testing workflows.
Work closely with engineering teams to productionize AI models and services.
Research and implement the latest advancements in computer vision, diffusion models, and multimodal AI systems.
Optimize models for inference speed, memory consumption, and scalability.
Develop robust APIs and model\-serving solutions for production environments.
Document experiments, model architectures, and deployment processes.
*Qualifications**
3\+ years of hands\-on experience in Machine Learning, Deep Learning, Computer Vision, and Generative AI.
Proven experience developing, optimizing, and deploying production\-grade AI solutions.
Strong expertise in computer vision models including RF\-DETR, DETR variants, YOLO family, Faster R\-CNN, Mask2Former, Segment Anything Model (SAM), semantic segmentation, instance segmentation, Depth Anything/Depth Anything V2, and monocular depth estimation.
Hands\-on experience with generative AI and diffusion models such as Stable Diffusion XL (SDXL), ControlNet, image inpainting/outpainting, image\-to\-image pipelines, LoRA training and fine\-tuning, and Hugging Face Diffusers.
Strong understanding of CNNs, Transformers, Vision Transformers (ViTs), attention mechanisms, and modern deep learning architectures.
Advanced proficiency in PyTorch, model training, fine\-tuning, hyperparameter optimization, and performance evaluation using metrics such as mAP, IoU, Precision, Recall, and F1 Score.
Strong Python programming skills with experience in FastAPI, Flask, or similar backend frameworks.
Experience with Docker, containerized deployments, Linux environments, Git, and collaborative development workflows.
Familiarity with cloud platforms such as AWS, GCP, Azure, or RunPod.
Experience in dataset preparation, augmentation, annotation, and quality control using tools such as CVAT, Label Studio, Roboflow, or similar platforms.
Knowledge of multimodal AI systems, vision\-language models (VLMs), MLOps practices, CI/CD pipelines, distributed training, and GPU optimization.
Familiarity with OpenCV, image processing techniques, and synthetic data generation workflows.
Experience working on projects involving virtual staging, furniture detection and removal, empty room generation, medical image segmentation, industrial inspection systems, depth\-aware image editing, real estate AI solutions, or multi\-model vision pipelines.
Strong analytical thinking, problem\-solving, research capabilities, and the ability to independently implement emerging AI technologies.
Excellent communication, collaboration, and technical documentation skills.