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

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

SafeSpace Globalchennai, tamil nadu, in
10 days ago
Job description

Location : Hyderabad, India

About the engagement

We’re building higher-order safety analytics on an NVIDIA-accelerated edge box (SafeCore) with ViPE on top. We need a senior CV consultant to harden multi-camera ReID linking , stabilize tracking, and add lightweight action cues (e.g., throw, shove, encircle) that feed our CEP / graph detectors.

Time : 4–10 hrs / week (flex). Location : Remote with occasional India / US time zone overlap.

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 (
  • Next steps : If interested please email your cover letter and resume to

    Ashwin at ashwin.jaiswal@safespaceglobal.ai

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    Consultant • chennai, tamil nadu, in

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