Computer Vision Engineer

• Build and fine-tune custom object      detection, segmentation, and tracking models and related architectures for      client- or product-specific use cases.
• Design data pipelines covering      collection, annotation (Roboflow, CVAT, Label Studio), augmentation, and      curation to produce training-ready datasets.
• Train and evaluate models using      PyTorch, optimizing for mAP, precision/recall, and latency targets      specific to each deployment.
• Optimize models for inference      using TensorRT, ONNX, and quantization (FP16/INT8) to hit real-time      performance on target hardware.
• Integrate vision models into      broader systems through REST/gRPC APIs, video stream processors (RTSP,      GStreamer), or edge runtimes.
• Monitor production models for      drift, edge cases, and failure modes; build retraining loops to keep      performance high over time.
• Collaborate with product,      hardware, and software teams to scope problems, set realistic      accuracy/latency targets, and ship.

 

Requirements

 What You Bring To The Table

• 3+ years of hands-on computer vision experience with at least one production deployment of a custom-trained detection or segmentation model.
• Strong Python skills and fluency  with PyTorch; comfortable reading and modifying model code, not just calling high-level APIs.
• Working knowledge of the NVIDIA stack: CUDA fundamentals, TensorRT, and at least one of DeepStream, Triton, or Jetson deployment.
• Experience with the full data lifecycle: sourcing imagery/video, designing annotation schemas, and handling class imbalance and edge cases.
• Solid grasp of evaluation metrics (mAP, IoU, confusion matrices) and what they actually mean for a given application.

Nice to Have

• Experience with multi-object tracking (ByteTrack, BoT-SORT, DeepSORT).
• Background in pose estimation,  OCR, or 3D vision.
• Familiarity with synthetic data generation (Omniverse Replicator, Unity Perception).
• MLOps experience: experiment  tracking (W&B, MLflow), CI/CD for models, containerization (Docker).
• Domain experience in security / law enforcement / military / intelligence
• Contributions to open-source CV projects.