- Jalan Gertak Merah Johor Bahru Johor Malaysia 80000

Working Location
Job Description
Requirements
Role Overview
We are looking for a versatile Applied AI Engineer to drive end-to-end computer vision initiatives across transit, mobility, and enterprise applications. This is a high-impact individual contributor role where you will work across the full AI development lifecycle — from integrating multimodal LLM APIs for rapid prototyping, to training and deploying optimized models on edge hardware, and building frontend/backend systems that bring these capabilities into production.
You will be involved in projects related to:
ANPR (Automatic Number Plate Recognition)
Vehicle damage detection
Document intelligence (eKYC, OCR)
Product quality inspection
Real-time vision systems
Responsibilities
Key Responsibilities
1. Multimodal LLM Integration & Prompt Engineering
Integrate and evaluate vision-capable LLM APIs such as OpenAI GPT-4oandGoogle Gemini Vertex for production vision tasks.
Design and optimize prompts to improve accuracy while minimizing token costs across use cases such as license plate recognition, document extraction, and visual quality control.
Benchmark commercial LLM solutions based on cost, latency, and accuracy to support build-vs-buy decisions.
2. Custom Model Development & Edge Optimization
Design and train task-specific AI models such as YOLO, OCR, and classification models as datasets mature.
Manage the full machine learning lifecycle, including:
Data labeling strategies
Training pipelines
Model versioning
Production monitoring (MLOps)
Optimize and deploy AI models on edge devices.
3. Agentic Full-Stack Development
Build frontend and backend systems to deliver AI vision capabilities to end users and business stakeholders.
Develop agentic workflows to automate multi-step AI processes (e.g., capture → inference → validation → action).
Deploy and maintain production-grade systems using modern frameworks and cloud infrastructure such as AWSandDocker.
4. Edge Device & Camera Hardware Integration
Configure and maintain edge devices connected to camera hardware and streaming pipelines.
Collaborate on camera sensor selection, lighting setup, and troubleshooting real-world image capture conditions.
Ensure system reliability and performance in field environments.
Requirements
Technical Skills
Strong programming skills in Python.
Experience integrating LLM APIs such as OpenAI, Gemini Vertex, or equivalent multimodal APIs.
Hands-on experience with computer vision libraries such as OpenCV.
Familiarity with prompt engineering techniques for vision-based AI tasks.
Experience with Docker and at least one cloud platform (AWS preferred).
Ability to build basic web-based or API-driven interfaces (e.g., FastAPI or similar frameworks).
Soft Skills
Strong communication and stakeholder management skills.
Strong problem-solving mindset with the ability to work independently.
Edge & Deployment
Exposure to deploying AI models on edge hardware is an added advantage.
Nice to Have
Experience with OCR pipelines or document intelligence solutions (e.g., eKYC, structured image extraction).
Exposure to synthetic data generation tools such as Stable DiffusionorGANs.
Experience with RTSP streams, camera integration, or real-time video pipelines.
Education & Experience
Bachelor’s or Master’s Degree in Computer Science, Electrical/Electronic Engineering, or related fields.
Candidates with hands-on AI/computer vision projects, internships, or portfolios are encouraged to apply.
Fresh graduates are welcome to apply.
Benefits
Skills
Important Information
Never provide your bank or credit card details when applying for jobs. Do not transfer any money or complete unrelated online surveys. If you see something suspicious, Report this Job ad.