Real-Time Computer Vision Systems Engineer

Wakapi; Departamento Capital; Presencial; ARS 1.200.000 - 2.400.000; Jornada completa

Descripción de la vacante

Wakapi seeks a seasoned computer vision engineer to design and deploy production‑level AI vision systems. You will develop state‑of‑the‑art detection models and real‑time pipelines for high‑throughput video and image streams, including LPR/OCR workflows.

You will optimize performance on cloud and edge devices, curate datasets, and establish automated retraining loops. Strong Python/DL framework skills and experience with modern architectures are essential.

Formación

• 3+ years of hands‑on CV and deep learning model deployment in production.
• Expertise with YOLO, DETR, Faster R‑CNN, Vision Transformers.
• Proficient Python and DL frameworks: PyTorch, OpenCV, TensorFlow.
• Experience with video stream ingestion and low‑latency inference.

Responsabilidades

• Model Architecture & Development: Design, train, and fine‑tune state‑of‑the‑art object detection models.
• Stream Processing & Pipeline Engineering: Build low‑latency ingestion and processing pipelines for high‑throughput video/image streams.
• Domain Application & LPR: Engineer end‑to‑end CV workflows including LPR/OCR and multi‑object tracking.
• Inference Optimization: Optimize execution on cloud (Kubernetes/GCP) and edge devices using TensorRT/ONNX/OpenVINO.
• Dataset & Active Learning: Curate, annotate, and augment datasets; automate retraining loops and evaluation.

Conocimientos

Computer Vision

Deep Learning

YOLO

DETR

PyTorch

OpenCV

TensorFlow

Python

Video Streams

LPR OCR

TensorRT

ONNX

OpenVINO

Kubernetes

GCP

Herramientas

TensorRT

ONNX

OpenVINO

Kubernetes

GCP

Descripción del empleo

Wakapi seeks a seasoned computer vision engineer to design and deploy production‑level AI vision systems. You will develop state‑of‑the‑art detection models and real‑time pipelines for high‑throughput video and image streams, including LPR/OCR workflows.

You will optimize performance on cloud and edge devices, curate datasets, and establish automated retraining loops. Strong Python/DL framework skills and experience with modern architectures are essential.