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Deep Learning Engineer (Computer Vision & Audio Analysis)

Deep Learning Engineer (Computer Vision & Audio Analysis)

Hubnex

3 - 8 years

6 - 10 Lacs

Bengaluru

Posted:2 days ago| Platform:

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Skills Required

Training Computer vision deep learning 3D Statistical analysis Programming Transformers Deployment Scheduling Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Deep Learning Engineer (Computer Vision & Audio Analysis)

Location: Remote / Client Location
Experience: 3+ Years
Employment Type: Full-Time (Client Deployment via Hubnex Labs)

Role Overview

Join a pioneering AI team to design and deploy cutting-edge deep learning solutions for computer vision and audio analysis. You ll leverage CNNs, Vision Transformers, attention mechanisms, and multi-modal techniques to solve complex real-world challenges in object detection, video processing, and audio classification.

Key Responsibilities

Design, develop, and optimize deep learning models for image/video analysis (object detection, segmentation) and audio classification tasks.
Implement and fine-tune CNN architectures , Vision Transformers (ViT, Swin), and attention mechanisms (SE, CBAM, self/cross-attention).

Process multi-modal data:

Video
: Apply spatiotemporal modeling (3D CNNs, temporal attention)
Audio
: Extract features (spectrograms, MFCCs) and build classification pipelines

Utilize pretrained models (transfer learning) and multi-task learning frameworks.
Optimize models for accuracy, speed, and robustness using PyTorch/TensorFlow.
Collaborate with MLOps teams to deploy solutions into production.

Required Skills

Programming : Advanced Python (PyTorch/TensorFlow)
Computer Vision :

Vision Transformers (ViT, Swin, DeiT)
Object detection (YOLO, SSD, Faster R-CNN, DETR)
Video analysis (temporal modeling)

Audio Processing : Feature extraction (MFCCs, spectrograms) and classification
Modeling Expertise :

Attention mechanisms (self/cross-attention, SE, CBAM)
Transfer learning and fine-tuning
Training strategies (LR scheduling, early stopping, data augmentation)

Experience handling large-scale datasets and building data pipelines.

Preferred Qualifications

Exposure to multi-modal learning (combining vision/audio/text)
Familiarity with R for statistical analysis
Publications or projects in CVPR/NeurIPS/ICML

This role is for a client of Hubnex Labs. Selected candidates will represent Hubnex while working directly with the client s AI team.

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Deep Learning Engineer (Computer Vision & Audio Analysis)