Senior Applied AI Engineer (Computer Vision)

AuxoAI Inc.; Bengaluru; Hybrid; INR 7,469,654 - 11,204,481; Full time

Job summary

A technological innovator in Bengaluru is seeking a Senior Applied AI Engineer to design and deploy production-grade computer vision systems. This role involves building end-to-end visual intelligence systems and requires a strong background in deep learning and system deployment. You will work on perception and reasoning tasks over visual data, integrating these capabilities into larger AI platforms. Ideal candidates will have over 5 years of experience in production environments and proficiency with frameworks like PyTorch or TensorFlow.

Qualifications

• 5+ years of experience in building production computer vision systems.
• Strong experience with deep learning frameworks.
• Hands-on experience with detection, segmentation, or tracking systems.

Responsibilities

• Design and deploy reliable computer vision systems.
• Build models using Vision Transformers.
• Integrate vision systems into agent-based workflows.

Skills

Deep learning frameworks (PyTorch / TensorFlow)

Computer vision systems

Object detection, segmentation, tracking

Multimodal systems (vision + language)

Job description

AuxoAI Engineering Pvt. Ltd. | Full time

Bangalore North, India | Posted on 04/06/2026

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)

Responsibilitiesp:

Design and deploy computer vision systems for tasks such as:

• Object detection, segmentation, and tracking
• Scene understanding and structured perception
• Video understanding and temporal reasoning

Build and optimize models using architectures such as:

• Vision Transformers (ViT, Swin, DeiT)

Develop multimodal systems combining vision and language:

• Visual grounding and captioning systems

Implement algorithms for:

• Multi‑object tracking (SORT, DeepSORT, ByteTrack)
• Feature matching and representation learning
• Temporal modeling (RNNs, Transformers for video)

Apply geometric and classical computer vision methods where relevant.

Optimize systems for:

• Throughput and scalability
• Edge and distributed deployment

Design and build data pipelines for:

• Dataset curation

Integrate vision systems into:

• Agent‑based systems

Requirements

• 5+ years of experience building computer vision systems in production environments
• Strong experience with deep learning frameworks (PyTorch / TensorFlow)
• Hands‑on experience with:
  • Detection, segmentation, or tracking systems
  • Model training, fine‑tuning, and evaluation
• Strong understanding of:
  • Representation learning
  • Loss functions (contrastive loss, focal loss, etc.)
  • Evaluation metrics (mAP, IoU, precision/recall)
• Experience building and deploying end‑to‑end vision systems, not just training models

Candidates 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 similar
• Experience with 3D vision:
  • NeRFs
  • SLAM
  • Point clouds
• Experience with video understanding:
  • Action recognition
  • Event detection
• Active learning
• Experience working with large‑scale datasets and distributed training pipelines