Computer Vision Engineer (Video Analytics, Python)
D
Dev.ProComputer vision, video analytics
São Paulo, São Paulo, Brazil. Buenos Aires, Buenos Aires, Argentina. Bogotá, Bogota, Colombia. Lima, Callao Region, PeruContractSenior
Salary not disclosed
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Job Details
- Languages
- Upper-Intermediate+ English level
- Experience
- 7+ years of software engineering experience; 3+ years of experience shipping computer vision solutions to production
- Required Skills
- PythonOpenCVPyTorchComputer Vision
Requirements
- Have 7+ years of software engineering experience with strong backend skills.
- Have 3+ years of experience shipping computer vision solutions to production.
- Demonstrate strong Python proficiency.
- Have experience with OpenCV, PyTorch, async I/O frameworks, and API integrations.
- Have hands-on experience with YOLO/Ultralytics or similar object detection frameworks.
- Have experience detecting, labeling, and tracking objects in video.
- Know frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation.
- Have experience optimizing GPU inference, including batching, stride, TensorRT, CUDA, quantization, and throughput tuning.
- Have upper-intermediate or higher English proficiency.
- Be able to communicate and collaborate effectively with engineering and product teams.
Responsibilities
- Develop and optimize GPU-accelerated video inference pipelines for real-time processing.
- Implement, evaluate, and improve YOLO or similar object detection models.
- Build temporal smoothing and tracking logic for safety-event detection.
- Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools.
- Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services.
- Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs.
- Contribute to dataset curation, labeling, and model evaluation, and fine-tune or train models as needed.
- Support containerized deployments with Docker and assist with monitoring and scaling production workloads.
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