Computer Vision, AI Systems Engineer

Wakapi

. Research, architect, and construct production AI vision systems .

Posted 9/29/2026full-timeMendoza • ArgentinaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying computer vision and deep learning models, with a focus on optimizing performance for cloud and edge environments. Proficient in building and managing end-to-end workflows for real-time video and image processing.

Highest-signal resume keywords

Computer Vision Model DevelopmentDeep Learning Frameworks (PyTorch, TensorFlow)Object Detection Architectures (YOLO, DETR, Faster R-CNN)Video Stream Ingestion and ProcessingLicense Plate Recognition (LPR) and OCR

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingModel OptimizationDeep Learning Model TrainingAttribute ExtractionModel Quantization

Tools & Technologies

TensorRTONNXOpenVINOOpenCV

Industry Keywords

Real-Time InferenceHigh-Throughput Video ProcessingAutomated Model RetrainingMulti-Object TrackingVisual Dataset Annotation

Tech Stack

Tools & technologies

CloudPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Research, architect, and construct production AI vision systems
Design, train, and fine-tune vision models for object detection, classification, and attribute extraction
Build low-latency ingestion and processing pipelines for high-throughput video and image streams
Engineer end-to-end computer vision workflows, including LPR/ANPR, OCR, and multi-object tracking
Optimize model performance for cloud infrastructure and edge devices using TensorRT, ONNX, or OpenVINO
Curate, annotate, and augment visual datasets
Establish automated model retraining loops and evaluation frameworks
Extract attributes and infer intelligence from image and video streams in real time

Requirements

What you’ll need

3+ years of hands-on experience designing and deploying computer vision and deep learning models in production environments
Deep expertise with modern object detection architectures (YOLO, DETR, Faster R-CNN, Vision Transformers)
Strong programming skills in Python and deep learning frameworks (PyTorch, OpenCV, TensorFlow)
Proven experience working with video stream ingestion, frame processing, and low-latency inference pipelines
Demonstrated experience with License Plate Recognition (LPR), OCR, or fine-grained attribute inference systems
Familiarity with model quantization, ONNX export, and TensorRT compilation for hardware acceleration

Benefits

Comp & perks

Excellent working conditions
Ever-evolving benefits package
Great working environment
Personalized career plans to achieve professional goals
Continuous training programs