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Dev.ProComputer Vision Engineer (Video Analytics, Python) - OP02259-OS
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Before you apply
LocationLima, Callao Region, Peru
Work moderemote
Typefull-time
SenioritySenior
Experience7+ yrs
DepartmentOP
Company size1,001–5,000 people
PostedNov 3, 2026 · 5d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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 (batching, stride, TensorRT, CUDA, quantization, 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
Familiarity with Docker, cloud deployments, and production monitoring systems
Experience in temporal/sequence analysis for event detection
Experience with video analytics in safety, compliance, or industrial/transportation environments
Skills
Python
OpenCV
PyTorch
YOLO/Ultralytics
TensorRT
ONNX
CUDA
Azure Event Hub
Azure Blob Storage
Application Insights
Docker
async I/O
About the company
New opportunities in Latin America!
🟢 Dev.Pro is a US-based software development company helping tech companies build their products and grow their business. We’re remote-first, and we work with independent contractors in over 55 countries, so you’d be collaborating in a multicultural environment on some really interesting projects.
About the role
We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions.
Benefits
🟩 What’s in it for you:
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Collaborate with top engineers on an innovative, technically challenging computer vision project
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Build impactful systems that enhance safety across large fleets and industrial operations
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Gain hands-on experience with GPU-accelerated video analytics, temporal tracking, and real-time safety monitoring
✅ Is that you?
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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 (batching, stride, TensorRT, CUDA, quantization, throughput tuning)
•
Ability to communicate and collaborate effectively with engineering and product teams
•
Upper-Intermediate+ English level
Desirable:
•
Experience with Azure Event Hub, Blob Storage, Application Insights, or similar
•
Familiarity with Docker, cloud deployments, and production monitoring systems
•
Experience in temporal/sequence analysis for event detection
•
Experience with video analytics in safety, compliance, or industrial/transportation environments
Responsibilities
🧩Key responsibilities and your contribution
In this role, you’ll develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models.
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Develop and optimize GPU-accelerated video inference pipelines for real-time processing
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Implement, evaluate, and improve object detection models (YOLO or similar)
•
Build temporal smoothing and tracking logic for safety event detection
•
Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools
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Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services
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Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs
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Contribute to dataset curation, labeling, and model evaluation; fine-tuning/training as needed
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Support containerized deployments (Docker) and assist with monitoring and scaling production workload
Our next steps:
✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Interview — ✅ Signing the Contract
Interested? Find out more:
📋 How to Join Us
💻 LinkedIn Page
📈 Our website
💻 IG Page
Legal
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