Vision AI Engineer

Job Description:

We are seeking a Senior Computer Vision Developer to design, build, and deploy vision-based AI solutions for real-world applications. The role requires deep hands-on experience with image/video analytics, deep learning model development, optimization, and deployment. You will work closely with AI Architects and data engineers to deliver high-performance, production-grade vision systems.

Experience Required

• 5–8 years of experience in AI/ML engineering, with 3+ years specialized in Computer Vision.
• Hands-on deployment of vision models in production environments (edge or cloud).
• Proven experience in optimizing models for real-time inference.
• Strong track record of building vision AI solutions for real-world use cases (retail, healthcare, manufacturing, autonomous systems, surveillance, etc.).

Key Responsibilities

• Model Development & Training
• Implement and fine-tune state-of-the-art computer vision models for object detection, classification, segmentation, OCR, pose estimation, and video analytics.
• Apply transfer learning, self-supervised learning, and multimodal fusion to accelerate development.
• Experiment with generative vision models (GANs, Diffusion Models, ControlNet) for synthetic data augmentation and creative tasks.
• Vision System Engineering
• Develop and optimize vision pipelines from raw data preprocessing → training → inference → deployment.
• Build real-time vision systems for video streams, edge devices, and cloud platforms.
• Implement OCR and document AI for text extraction, document classification, and layout understanding.
• Integrate vision models into enterprise applications via REST/gRPC APIs or microservices.
• Optimization & Deployment
• Optimize models for low-latency, high-throughput inference using ONNX, TensorRT, OpenVINO, CoreML.
• Deploy models on cloud (AWS/GCP/Azure) and edge platforms (NVIDIA Jetson, Coral, iOS/Android).
• Benchmark models for accuracy vs performance trade-offs across hardware accelerators.
• Data & Experimentation
• Work with large-scale datasets (structured/unstructured, multimodal).
• Implement data augmentation, annotation pipelines, and synthetic data generation.
• Conduct rigorous experimentation and maintain reproducible ML workflows.

Required Skills & Qualifications

• Programming: Expert in Python; strong experience with C++ for performance-critical components.
• Deep Learning Frameworks: PyTorch, TensorFlow, Keras.
• Computer Vision Expertise:
• Detection & Segmentation: YOLO (v5–v8), Faster/Mask R-CNN, RetinaNet, Detectron2, MMDetection, Segment Anything.
• Vision Transformers: ViT, Swin, DeiT, ConvNeXt, BEiT.
• OCR & Document AI: Tesseract, PaddleOCR, TrOCR, LayoutLM/Donut.
• Video Understanding: SlowFast, TimeSformer, action recognition models.
• 3D Vision: PointNet, PointNet++, NeRF, depth estimation.
• Generative AI for Vision: Stable Diffusion, StyleGAN, DreamBooth, ControlNet.
• MLOps Tools: MLflow, Weights & Biases, DVC, Kubeflow.
• Optimization Tools: ONNX Runtime, TensorRT, OpenVINO, CoreML, quantization/pruning frameworks.
• Deployment: Docker, Kubernetes, Flask/FastAPI, Triton Inference Server.
• Data Tools: OpenCV, Albumentations, Label Studio, FiftyOne.