AI/ML Engineer

Experience Required: 3-8 Years No. of vacancies: 2 Job Type: Full Time Vacancy Role: WFO 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. 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. Skills:- Computer Vision, Generative AI, Deep Learning, Machine Learning (ML) and Convolutional Neural Network (CNN)