Vacancy description
₺3 TRY
India, Gurugram
Auxo AI - Senior Applied AI Engineer - Computer Vision in Gurugram, India is listed on Jobeax. Browse 30,000+ vacancies available.
Job Description :AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world https://jobeax.com/link/SFg0hEiyYqQPdzCu 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 https://jobeax.com/link/PYRlShoTK42JUOHt will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based https://jobeax.com/link/INsJOvbWZUnhOf7E 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 https://jobeax.com/link/PWiCmSRDPN3j9Xo9 : Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid - 3 days per week in office)Responsibilities :- Design and deploy computer vision systems for tasks such as :1. Object detection, segmentation, and tracking2. Scene understanding and structured perception3. Video understanding and temporal reasoning- Build and optimize models using architectures such as :1. CNNs (ResNet, EfficientNet)2. Vision Transformers (ViT, Swin, DeiT)3. Detection/segmentation models (YOLO, DETR, Mask R-CNN)- Develop multimodal systems combining vision and language :1. CLIP-style models2. Vision-language models (VLMs)3. Visual grounding and captioning systems- Implement algorithms for :1. Multi-object tracking (SORT, DeepSORT, ByteTrack)2. Feature matching and representation learning3. Temporal modeling (RNNs, Transformers for video)- Apply geometric and classical computer vision methods where relevant :1. Camera calibration2. Epipolar geometry3. Pose estimation4. 3D reconstruction or depth estimation- Optimize systems for :1. Low-latency, real-time inference2. Throughput and scalability3. Edge and distributed deployment- Design and build data pipelines for :1. Annotation workflows2. Dataset curation3. Synthetic data generation- Integrate vision systems into :1. Multimodal AI pipelines2. Agent-based systems3. Decision-making workflowsRequirements :- 5+ years of experience building computer vision systems in production environments- Strong experience with deep learning frameworks (PyTorch / TensorFlow)- Hands-on experience with :1. Detection, segmentation, or tracking systems2. Model training, fine-tuning, and evaluation- Strong understanding of :1. Representation learning2. Loss functions (contrastive loss, focal loss, etc.)3. Evaluation metrics (mAP, IoU, precision/recall)4. 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 https://jobeax.com/link/BnTBmK5prlfIDtS0 to Have :- Experience with multimodal systems (vision + language)- Familiarity with models such as :1. CLIP, BLIP, Flamingo, or similar- Experience with 3D vision :1. NeRFs2. SLAM3. Point clouds- Experience with video understanding :1. Action recognition2. Event detection- Experience building data engines :1. Active learning2. Hard negative mining3. Experience working with large-scale datasets and distributed training pipelines (ref:hirist.tech)
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