Computer Vision Engineer, Video Analytics, Python

Job not on LinkedIn

🔥 2 minutes ago

🌐 Brazil, Argentina, +2 more countries – Remote

🇧🇷 Brazil – Remote 🇦🇷 Argentina – Remote 🇨🇴 Colombia – Remote 🇵🇪 Peru – Remote

⏳ Contract/Temporary

🟠 Senior

🔴 Lead

👁️ Computer Vision Engineer

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Dev.Pro

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2011

🏥 Healthcare

🏨 Hospitality

📦 Logistics

Healthcare • Hospitality • Logistics

Dev. Pro is a software development partner that supports technology companies with custom outsourced software development services. With over 13 years of experience, a team of more than 900 experts, and operations in over 50 countries, Dev. Pro provides a comprehensive range of services including cloud development, DevOps, software testing and QA, system integration, and application security. The company caters to a wide array of industries such as digital commerce, fintech, hospitality, and healthcare by delivering tailored software development experiences. Dev. Pro emphasizes quality, innovation, and a transparent collaboration process to accelerate growth for ambitious startups and Fortune 500 enterprises alike, ensuring successful outcomes through a well-balanced and efficient team approach.

📋 Description

• Develop and optimize GPU-accelerated video inference pipelines for real-time processing • Implement, evaluate, and improve object detection models such as YOLO • 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; fine-tune or train models as needed • Support containerized deployments with Docker and assist with monitoring and scaling production workloads • Collaborate with engineering and product teams to deliver reliable, high-performance video analytics solutions

🎯 Requirements

• 7+ years of software engineering experience with strong backend skills • 3+ years of experience shipping computer vision solutions to production • Strong Python proficiency • Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations • Hands-on experience with YOLO/Ultralytics or similar object detection frameworks • Experience detecting, labeling, and tracking objects in video • Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation • Experience with GPU inference optimization, including batching, stride, TensorRT, CUDA, quantization, and throughput tuning • Ability to communicate and collaborate effectively with engineering and product teams • Upper-Intermediate+ English level • Experience with Azure Event Hub, Blob Storage, Application Insights, or similar (desirable) • Familiarity with Docker, cloud deployments, and production monitoring systems (desirable) • Experience in temporal/sequence analysis for event detection (desirable) • Experience with video analytics in safety, compliance, or industrial/transportation environments (desirable) • CV must be submitted in English

🏖️ Benefits

• Collaborate with top engineers on an innovative, technically challenging computer vision project • Build impactful systems that enhance safety across large fleets and industrial operations • Gain hands-on experience with GPU-accelerated video analytics, temporal tracking, and real-time safety monitoring • Remote-first work environment • Independent contractor engagement • Multicultural environment • Opportunity to work with engineering and product teams on real-world systems

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