全职 Machine Learning & Applied AI Engineer 工作, 薪水 up to MYR 6,000, Career Horizons Johor 公司招聘中 - Ricebowl

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

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.

• 13th Month Bonus
• Opportunities for promotion
• Professional development
• Annual Leave
• Medical and Hospitalisation Leave
• EPF
• SOCSO
• EIS
• Annual Bonus
• Performance Bonus
• 5 Working Days
• Medical Insurance
• Training Provided