Computer Vision Engineer
Software Engineering
United States
Posted on Aug 5, 2026
hackajob is collaborating with Leo Technologies to connect them with exceptional professionals for this role.
What You Bring To The Table
- 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.
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.
- 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.