Computer Vision Consultant (ReID / Action Recognition) — Part-Time

5 years

0 Lacs

hyderabad telangana india

Posted:2 days ago| Platform: Linkedin logo

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Skills Required

vision recognition analytics tracking flex design export normalization management geometry deployment quantization evaluation metrics latency data strategy pytorch tuning cam profiling cuda inference server onnx masking apache calibration report ide stability

Work Mode

Remote

Job Type

Full Time

Job Description

Location

About the engagement

ReID linking

Time

What you’ll do

  • Design and tune

    cross-camera ReID

    pipelines: embedding export, normalization, gallery management, thresholding per zone/time band.
  • Stabilize tracking (ByteTrack / OC-SORT / StrongSORT) and hand-off signals for CEP.
  • Add

    light action heads

    (pose+trajectory) for “throw”, “shove/push”, “handoff”, “encircle geometry assist”.
  • Optimize for edge: INT8/FP16 deployment (TensorRT/Triton), pruning/quantization, batch & stream concurrency.
  • Define

    evaluation harness

    : ROC/PR per zone, re-link rate, ID-switch metrics, latency budget adherence.
  • Advise on data strategy: mining hard negatives, synthetic augmentation, and privacy-safe curation.

Must-have

  • 5+ years in CV for detection/tracking/ReID; shipped models in production.
  • Strong with PyTorch; experience with

    TorchReID/FastReID

    and

    TensorRT/DeepStream

    .
  • Tracker tuning (NMS/iou/appearance-matching) and multi-cam association.
  • Performance profiling (Nsight Systems/Compute), real-time constraints.

Nice-to-have

  • CV-CUDA, Triton Inference Server, ONNX export; pose frameworks (RTM-Pose/OpenPifPaf).
  • Experience with privacy-preserving analytics (masking, on-device embeddings).
  • Familiarity with Apache-friendly/open licenses for models & datasets.

Deliverables (first 4–6 weeks)

  • ReID linking tuned with zone-specific thresholds + metrics board.
  • Action cues (throw/shove/encircle-assist) producing event confidences ≤30 ms/frame on target GPU.
  • Written calibration & retraining SOP + benchmark report (latency, ID-switch, precision/recall).

Selection Criteria:

·     Live/Whiteboard/IDE (90-120 min) around Multi-cam ReID thresholding & linking, Tracker stability & ID-switch control, Lieghtweight “throw” action head and Deployment & profiling

·     Take-Home (< 6hours, due in 48h)


Next steps

Ashwin at ashwin.jaiswal@safespaceglobal.ai

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