Computer Vision Engineer (Video Analytics, Python) - OP02259-OS
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked just now — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 11h ago
The date the source published, not the day we noticed it (2026-11-03). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Brazil, Argentina, Colombia, Peru
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $3,250–7,250/mo
Middle 50% of 69 listings that do state pay — Engineering · all levels · LATAM · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workable employer's own board first seen just now · last seen just now
The listing
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.
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.
🟩 What's in it for you:
- 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
✅ Is that you?
- 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
🧩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.
- Develop and optimize GPU-accelerated video inference pipelines for real-time processing
- 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
- 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-tuning/training as needed
- 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:
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