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Computer Vision Engineer (Freelancer)

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Onsite

Computer Vision Engineer (Freelancer)

Soul Ai

Computer Vision Engineer (Freelancer)

Skills

Google Cloud PlatformDeep LearningDockerPythonMicroservicesNumPyPyTorchTensorFlowRMachine LearningAIAWSKubernetesAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

15 September 2026

What they need


We are looking for Indias top 1% Computer Vision Engineers for a unique job opportunity to work with the industry leaders.- Who can be a part of the community. We are looking for top-tier Computer Vision (CV) Engineers with expertise in image/video processing, object detection, and generative AI. If you have experience in this field then this is your chance to collaborate with industry leaders.

  • Whats in it for you. Pay above market standards. The role is going to be contract based with project timelines from 2 12 months, or freelancing.
  • Be a part of an Elite Community of professionals who can solve complex AI challenges.
  • Work location could be:. Remote (Highly likely). Onsite on client location. Deccan AIs OfficeHyderabad or Bangalore. Responsibilities:. Develop and optimize computer vision models for tasks like object detection, image segmentation, and multi-object tracking.
  • Lead research on novel techniques using deep learning frameworks (TensorFlow, PyTorch, JAX).
  • Build efficient computer vision pipelines and optimize models for real-time performance.
  • Deploy models using microservices (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
  • Lead MLOps practices, including CI/CD pipelines, model versioning, and training optimizations.
  • Required Skills:
  • . Expert in Python, OpenCV, NumPy, and deep learning architectures (e.g., ViTs, YOLO, Mask R-CNN).
  • Strong knowledge in computer vision fundamentals, including feature extraction and multi-view geometry with experience in deploying and optimizing models with TensorRT, Open VINO, and cloud/edge solutions.
  • Proficient with MLOps tools (ML flow, DVC), CI/CD, and distributed training frameworks.
  • Experience in 3D vision, AR/VR, or LiDAR processing is a plus.
  • Nice to Have:. Experience with multi-camera vision systems, LiDAR, sensor fusion, and reinforcement learning for vision tasks.
  • Exposure to generative AI models (e.g., Stable Diffusion, GANs) and large-scale image processing (Apache Spark, Dask).
  • Research publications or patents in computer vision and deep learning.

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