Founding Senior Computer Engineer

Flatgigs; Abu Dhabi; Hybrid; AED 360,000 - 480,000; Full time

Benefits offered by this job

Remote friendly

Competitive package

Travel to Dubai for milestones

Job summary

Flatgigs is seeking a senior computer vision lead to own the end-to-end CV platform, from camera ingestion through detection, tracking, OCR, and reporting. You will push live product deployments and architect cross-industry solutions on the same stack.

You will guide model selection, training strategy, and annotation workflows while coordinating with senior engineers to ship robust, scalable systems with on-prem and cloud components. Travel to Dubai for milestones is expected.

Qualifications

• 5+ years building computer vision systems in production.
• Strong Python and PyTorch, with modern detection and tracking.
• Experience with RTSP/IP cameras and streaming inference.
• Built datasets with annotation pipelines and ground-truth evaluation.
• Experience fine-tuning open-source models and replacing with custom models.

Responsibilities

• Own the shared CV platform end to end: ingestion, detection, tracking, OCR, classification, and reporting.
• Ship to a live product from week one, improving accuracy with real users.
• Architect model selection, training strategy, annotation and dataset operations, evaluation methods.
• Deploy the new industry deployments and harden both products as one platform.
• Provide technical leadership of the engineering team.

Skills

Computer vision

Python

PyTorch

Production deployments

Camera/Vision systems

OpenCV

Dataset annotation

RTSP/Streaming video

Model evaluation

Tools

YOLO family

ByteTrack/DeepSORT

FFmpeg

ONVIF/RTSP

Roboflow

Job description

Job Description

About the company. Our client does AI match analysis for youth football. Fixed cameras at the pitch record every session. The models detect the events (passes, shots, goals), track the players, and read jersey numbers off low-res footage. Academies and parents get match stats, highlights and a per-player record. This is running today at a pilot academy in Dubai, on real matches, with paying pilots. They are now taking the same stack into a second industry. First customers are committed; details in conversation. This hire owns the platform across both: making the live sports models better, and building the new product on the same foundations.

What you own

• The shared CV platform, end to end: camera ingestion, detection and tracking, OCR, classification, and the reporting pipeline. It powers a product in production today and a second one launching.
• From week one you ship to a live product: raising accuracy on the sports models with real users, while architecting the second industrys deployment on the same stack.
• Architecture: model selection and training strategy, annotation and dataset operations, evaluation methodology, the on-prem/cloud split.
• Shipping the new industrys first deployments, then hardening both products as one platform.
• Technical leadership of the engineering team we build under you.

Hiring process

• Intro conversation: walk us through a CV system you built. Decisions, failures, numbers.
• Technical deep-dive with senior engineers.
• Case study on real footage: spec and prototype a detection task.
• Founders conversation, then offer.

The whole process inside two weeks for the right person.

What we need to see

• 5+ years building computer vision systems that ran in production. Deployed systems with users, not notebooks.
• Strong Python and PyTorch, hands-on with modern detection and tracking (YOLO family, ByteTrack/DeepSORT or similar).
• Video pipeline experience: RTSP/IP cameras, scheduled or streaming inference, ffmpeg-level fluency.
• You have built datasets, run annotation operations, and measured models honestly against ground truth.
• You have fine-tuned open-source models (detection, OCR of the PaddleOCR/TrOCR class) and taken the next step: replacing them with your own models trained on validated annotations, with a working annotation-review loop.
• Fluent in the modern CV tooling ecosystem: Roboflow or equivalent for dataset and annotation operations, experiment tracking, model registries.
• Ownership temperament: you take a vague operational goal and return a working system without waiting for a spec.

Strong pluses

• OCR, action recognition or pose estimation in production.
• Sports, retail, industrial or facility camera-analytics background.
• Edge deployment (Jetson or similar) and cost engineering of inference.
• Camera and IoT literacy: sensor and lens selection, PoE networking, ONVIF/RTSP, NVRs, weatherproof housings. You can spec a site, not just a model.

Full-time. Remote friendly: we hire the best person, not the nearest. Working hours overlapping the Gulf, with travel to Dubai for installation and milestone weeks. Competitive package plus options.