Go-To-Market Ai Systems Engineer

Somniosoftware; Ciudad de Mendoza; Presencial; ARS 1.800.000 - 2.400.000; Jornada completa

Descripción de la vacante

Somniosoftware seeks a Senior Computer Vision Engineer to design and deploy production-grade AI vision systems that operate on real-time image and video streams. You will architect detection models, train on diverse datasets, and build high-throughput, low-latency pipelines for cloud and edge environments.

You will work with YOLO variants, DETR, and Vision Transformers, optimizing models with TensorRT/ONNX and validating performance on streaming data sources.

Formación

• 3+ years hands-on experience designing and deploying computer vision models in production.
• 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 with video stream ingestion, frame processing, and low-latency inference.
• Experience with LPR/OCR or fine-grained attribute inference systems.
• Familiarity with model quantization, ONNX export, and TensorRT compilation for hardware acceleration.

Responsabilidades

• Research, architect, and build production AI vision systems for real-time attribute extraction from image and video streams.
• Design and fine-tune state-of-the-art vision models (YOLO variants, DETR, Transformers).
• Develop low-latency streaming pipelines (RTSP, WebRTC) for high-throughput data.
• Implement LPR/OCR and multi-object tracking components and optimize for cloud and edge deployment.
• Experiment with quantization, ONNX export, and TensorRT for hardware acceleration.

Herramientas

Python

PyTorch

OpenCV

TensorFlow

YOLO

DETR

Faster R-CNN

Vision Transformers

TensorRT

ONNX

Descripción del empleo

The Role:

Researches, architectures, and constructs production AI vision systems, leveraging state-of-the-art detection models and stream processing pipelines to extract attributes and infer intelligence from image and video streams in real time.

Model Architecture & Development: Design, train, and fine-tune state-of-the-art vision models (e.g., YOLO variants, DETR, Transformers) for object detection, classification, and attribute extraction.

Stream Processing & Pipeline Engineering: Build low-latency ingestion and processing pipelines for high-throughput video and image streams (e.g., RTSP, WebRTC, frame decoding).

Plate Recognition (LPR/ANPR), Optical Character Recognition (OCR), and multi-object tracking (MOT).

Inference Optimization: Optimize model performance for efficient execution on cloud infrastructure (Kubernetes/GCP) and edge devices using TensorRT, ONNX, or OpenVINO.

Dataset & Active Learning: Curate, annotate, and augment visual datasets, establishing automated model retraining loops and evaluation frameworks.

Requirements:

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

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.

YOLO / DETR | Computer Vision | PyTorch / OpenCV | Video Stream Processing | LPR / OCR |