Data Scientist

Role Overview

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.

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.

Requirements

• 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.
• Strong Python programming skills with experience in FastAPI, Flask, or similar backend frameworks.
• Experience with Docker, containerized deployments, Linux environments, and Git.
• Familiarity with cloud platforms such as AWS, GCP, Azure, or RunPod.
• Experience in dataset preparation, augmentation, and annotation using tools such as CVAT, Label Studio, or Roboflow.
• Knowledge of multimodal AI systems, vision-language models (VLMs), MLOps practices, CI/CD pipelines, and GPU optimization.
• Familiarity with OpenCV and image processing techniques.

Skills

• PyTorch
• Python
• FastAPI
• Docker
• AWS

Benefits

• Flexible schedule
• Leave encashment
• Provident Fund