AI/Machine Learning Engineer (Computer Vision & VLLMs)
Skills
About This Role
Role Overview
We are seeking a specialized AI/Machine Learning Engineer to lead the automation of AI system.
You will be responsible for processing and analyzing high-volume image data captured from thousands of network cameras.
The core of this role involves building automated data-cleaning pipelines and fine-tuning Vision Large Language Models (VLLMs) to analyze complex parking scenarios, seamlessly integrating these insights with our existing third-party OCR systems.
Key Responsibilities
**Data Pipeline & Automation:** Design and deploy automated pipelines to ingest, filter, and clean interval-based image data.
Implement pre-processing models (e.g., YOLO, SSD, or custom classifiers) to automatically identify and discard low-quality, redundant, or irrelevant images before they reach the main analysis engine.
**VLLM Implementation:** Select, fine-tune, and deploy open-source Vision Large Language Models (e.g., LLaVA, Qwen-VL) to evaluate complex scenarios without human intervention.
**Model Optimization:** Optimize the AI models for fast inference and scalability to handle thousands of concurrent image streams efficiently.
**Collaboration:** Work closely with backend developers and systems engineers to ensure smooth API integration and deployment into the existing production infrastructure.
Required Qualifications
- Experience: 3+ years in Machine Learning, AI Engineering, or a heavily focused Computer Vision role.
- Technical Skills: Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
- Hands-on experience with Vision-Language Models (VLLMs) or Large Multimodal Models (LMMs).
- Proven experience with traditional Computer Vision techniques and object detection models (YOLO, ResNet, etc.) for image classification and filtering.
- Data Handling: Experience managing and cleaning large-scale, unstructured image datasets.
- System Architecture: Understanding of how to build and deploy ML models into production environments (Docker, FastAPI, cloud or edge deployments).
- Nice to Have:
- Previous experience working with traffic monitoring, smart city infrastructure, or parking management systems.
- Familiarity with handling time-series image data or edge-computing environments.
Application Question(s)
- Can you start immediately?
Experience
- Information Technology: 3 years (Required)
- Ai/Machine Learning: 3 years (Required)
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