Senior Applied AI Engineer (Computer Vision)

AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.This role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, and multimodal models. It is not limited to model training and requires strong ownership of system design, deployment, and real-world performance.You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.You will also work on problems where existing approaches may not be sufficient, and will be expected to combine deep learning, geometric methods, and multimodal reasoning to build robust, production-grade systems.Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)Responsibilities:Design and deploy computer vision systems for tasks such as:Object detection, segmentation, and trackingScene understanding and structured perceptionVideo understanding and temporal reasoningBuild and optimize models using architectures such as:CNNs (ResNet, EfficientNet)Vision Transformers (ViT, Swin, DeiT)Detection/segmentation models (YOLO, DETR, Mask R-CNN)Develop multimodal systems combining vision and language:CLIP-style modelsVision-language models (VLMs)Visual grounding and captioning systemsImplement algorithms for:Multi-object tracking (SORT, DeepSORT, ByteTrack)Feature matching and representation learningTemporal modeling (RNNs, Transformers for video)Apply geometric and classical computer vision methods where relevant:Camera calibrationEpipolar geometryPose estimation3D reconstruction or depth estimationOptimize systems for:Low-latency, real-time inferenceThroughput and scalabilityEdge and distributed deploymentDesign and build data pipelines for:Annotation workflowsDataset curationSynthetic data generationIntegrate vision systems into:Multimodal AI pipelinesAgent-based systemsDecision-making workflowsRequirements:5+ years of experience building computer vision systems in production environmentsStrong experience with deep learning frameworks (PyTorch / TensorFlow)Hands-on experience with:Detection, segmentation, or tracking systemsModel training, fine-tuning, and evaluationStrong understanding of:Representation learningLoss functions (contrastive loss, focal loss, etc.)Evaluation metrics (mAP, IoU, precision/recall)Experience building and deploying end-to-end vision systems, not just training modelsCandidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.Nice to Have:Experience with multimodal systems (vision + language)Familiarity with models such as:CLIP, BLIP, Flamingo, or similarExperience with 3D vision:NeRFsSLAMPoint cloudsExperience with video understanding:Action recognitionEvent detectionExperience building data engines:Active learningHard negative miningExperience working with large-scale datasets and distributed training pipelines