Job Description:

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.

Key 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.

Required Skills & Qualifications:

Experience:

- 3+ years of hands-on experience in Machine Learning, Deep Learning, or Computer Vision.

- Proven experience developing and deploying production-grade AI solutions.

Computer Vision Expertise:

- RF-DETR

- DETR variants

- YOLO family

- Faster R-CNN

- Mask2Former

- Segment Anything Model (SAM)

- Semantic and Instance Segmentation

- Depth Anything / Depth Anything V2

- Monocular Depth Estimation

Generative AI & Diffusion Models:

- Stable Diffusion XL (SDXL)

- ControlNet

- Image Inpainting and Outpainting

- Image-to-Image Pipelines

- LoRA Training and Fine-tuning

- Hugging Face Diffusers

Machine Learning & Deep Learning:

- Strong understanding of CNNs, Transformers, Vision Transformers (ViTs), and Attention Mechanisms.

- Expertise in PyTorch.

- Experience with model training, fine-tuning, and hyperparameter optimization.

- Understanding of mAP, IoU, Precision, Recall, and F1 Score.

Engineering Skills:

- Advanced Python programming skills.

- Experience with FastAPI or similar frameworks.

- Docker and containerized deployments.

- Linux environments.

- Git and collaborative development workflows.

- Cloud platforms such as AWS, GCP, Azure, or RunPod.

Data Handling:

- Dataset preparation, augmentation, annotation, and quality control.

- Experience with CVAT, Label Studio, Roboflow, or similar tools.

Preferred Qualifications:

- Experience with multimodal AI systems and vision-language models.

- Knowledge of MLOps practices and CI/CD pipelines.

- Experience with distributed training and GPU optimization.

- Familiarity with OpenCV and image processing.

- Experience with synthetic data generation.

Preferred Project Experience:

- Virtual Staging Systems

- Furniture Detection and Removal

- Empty Room Generation

- Medical Image Segmentation