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Open nowPosted 289 days ago

Data Scientist (Computer Vision)

Scry AI22 open roles

Where
Gurgaon
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Your applicationOpen nowData Scientist (Computer Vision)Scry AI · Gurgaon

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 289 days ago

The posting

Please refer to the Company Website - https://scryai.com/careers/?q=jobs

Must Have:

  • Strong hands-on experience with deep learning-based computer vision, including object detection, classification, tracking, and real-time video analytics
  • Practical experience with CNN-based architectures such as YOLO (v5/v8) or similar, and ability to train, fine-tune, and evaluate models using PyTorch or TensorFlow
  • Experience building real-time vision pipelines for live video feeds (CCTV / streaming video) with low-latency constraints
  • Solid understanding of video analytics concepts including frame sampling, motion analysis, temporal consistency, and object tracking across frames
  • Strong understanding of image and video preprocessing pipelines including augmentation, normalization, and handling real-world data challenges such as low light, occlusion, motion blur, and varying camera angles
  • Hands-on experience deploying CV models on edge devices such as NVIDIA Jetson, Raspberry Pi, or similar embedded platforms
  • Exposure to model optimization techniques for edge deployment including quantization, pruning, or use of lightweight architectures
  • Ability to design and own end-to-end CV pipelines, from data ingestion and annotation to inference, monitoring, and performance evaluation in production
  • Experience working with Vision-Language Models (VLMs) or vision-enabled LLMs, and integrating vision model outputs with LLM pipelines for reasoning, event understanding, or summarization
  • Experience collaborating with backend and DevOps teams for production deployment, including familiarity with Docker and basic MLOps practices
  • Ability to evaluate and monitor model performance in production using appropriate computer vision metrics

Good to Have:

  • Experience with edge inference frameworks such as ONNX, TensorRT, or OpenVINO
  • Hands-on experience with video streaming and processing frameworks such as OpenCV, RTSP, GStreamer, or similar
  • Exposure to multimodal AI systems combining vision with text (and optionally audio)
  • Experience with multi-camera setups, camera calibration, or scene-level analytics
  • Familiarity with LLM orchestration frameworks such as LangChain or LlamaIndex
  • Understanding of edge AI security, privacy, and data compliance considerations in surveillance or industrial environments
  • Experience working on real-world CV deployments in domains such as smart cities, retail analytics, industrial monitoring, safety systems, or large-scale surveillance.
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