LLM Jobs | Вакансии по AI

We are seeking a highly experienced Computer Vision / Machine Learning Engineer to develop a human intrusion detection system from scratch as part of a governmental project.

This is a structured, security-focused engagement. The selected engineer will be responsible for designing and implementing a proprietary intrusion detection module that will serve as the foundation for a larger AI video analytics platform.

Successful delivery of this IDS module will lead to expanded development of additional models, long-term collaboration, increased financial scope, and potential relocation opportunities depending on performance and project progression.

Project Context

This engagement is related to a governmental request involving AI-based security analytics.

The initial objective is to develop a high-performance Intrusion Detection System (IDS) capable of real-time human detection within defined zones and virtual perimeters.

If Phase 1 (Intrusion Detection) is delivered successfully and validated, the roadmap includes development of additional models and modules within the same system architecture.

Core Requirements

The engineer must:

* Design and implement the intrusion detection architecture from scratch
* Structure the full training pipeline
* Implement polygon-based restricted zone logic
* Implement virtual line-crossing logic
* Support optional direction-based rules
* Handle partial body visibility cases
* Exclude animals and environmental motion
* Generate structured JSON event outputs
* Ensure real-time or near real-time inference

This is not a plug-and-play integration project. We expect clean architectural thinking and custom logic development.

Use of open-source detection backbones (YOLO, DETR, etc.) is acceptable if technically justified, but the intrusion logic, event system, and pipeline must be custom-developed.

Technical Expectations

* Strong background in Python
* Advanced experience with PyTorch or TensorFlow
* Experience in real-time video processing (RTSP)
* Experience in detection + tracking systems
* Experience optimizing inference latency
* Ability to build modular, production-ready code
* Experience with Docker/containerized deployment preferred

Infrastructure & IP

All development, training, datasets, model weights, and repositories will be managed within a controlled infrastructure environment due to the nature of the project.

Deliverables (Phase 1 – IDS)

* Full source code
* Training and inference scripts
* Trained model weights
* Performance evaluation report (Precision, Recall, F1)
* Deployment documentation

Performance targets will be defined and agreed upon before final validation.

LONG TERM OPPORTUNITY FOR THE REST
This is not a short-term isolated task.

If the Intrusion Detection module is successfully delivered and validated:

* Additional AI models will be developed
* Scope and financial compensation will significantly increase
* Long-term structured collaboration is expected
* Potential relocation options may be discussed depending on project expansion

We are looking for someone who sees this as a strategic opportunity, not a one-off freelance task.

Please include:

* Relevant computer vision projects
* Your proposed architectural approach
* Estimated timeline (preferably 3-4 weeks)

BUDGETING; TBD

telegram: @asinistrapelevin

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