Artificial Intelligence / Computer Vision Engineer

POROLIS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

POROLIS TECHNOLOGIES PTE. LTD. is seeking an experienced ML/CV engineer to develop computer vision applications for gemstones and build domain-specific LLM solutions. The role involves data preparation, model training, and end-to-end deployment across cloud and on-prem stacks.

You will collaborate with a cross-functional team of engineers and data scientists, working on modern architectures (ViT, DETR, CLIP) and MLOps workflows to deliver scalable AI solutions.

Qualifications

• Bachelor’s or Master’s degree in computer science, data science, artificial intelligence or related engineering fields.
• Minimum 3 to 5 years of proven experience in developing ML/DL architectures to solve real-world computer vision problems.
• Strong proficiency in Python with hands-on experience in mainstream deep learning frameworks (PyTorch and TensorFlow) and their associated computer vision libraries (e.g., OpenCV, torchvision, timm, Hugging Face Transformers).
• Experience in computer vision with OpenCV and modern deep learning architectures, with emphasis on ViT-based models (e.g., DETR, DINOv2, SAM) and vision-language models like CLIP.
• In-depth understanding of digital image processing, image transformation techniques, real-time image analytics and feature extraction.
• Experience in large-scale image data processing and data pipelines.
• Data storytelling, information visualization and technical writing skills.
• Hands-on experience with cloud platforms (AWS, GCP) and backend/serving stacks (FastAPI, Redis, Docker) for end-to-end AI model development and deployment.
• Strong prompt-engineering skills and ability to leverage AI-assisted development workflows.
• Excellent communication and collaboration skills.

Responsibilities

• Develop machine learning computer vision applications in object detection, classification, segmentation and recognition for gemstones.
• Develop LLM-applications specific to gemstone domain leveraging latest frameworks.
• Define dataset requirements and prepare documents for model training.
• Collaborate with IOT-product engineers, ML & data scientists, and software engineers to deploy solutions.
• Develop a comprehensive MLOps environment to manage lifecycle and pipeline of ML projects.
• Conduct research and product development with gatekeeping processes and handover to downstream teams.
• Execute data preparation, model building, testing, validation and deployment for scalable AI solutions.

Skills

Python

Deep Learning

Computer Vision

LLM / AI

Data Visualization

Technical Writing

Cloud Computing

MLOps

Prompt Engineering

Education

Bachelor’s or Master’s degree in Computer Science / Data Science / AI or related field

Tools

PyTorch

TensorFlow

OpenCV

torchvision

timm

Hugging Face Transformers

CLIP / ViT models

AWS / GCP

FastAPI

Redis

Docker

Claude Code / Cursor / Copilot

GitHub Copilot

Job description

Job responsibilities:

• Develop machine learning computer vision applications in object detection, classification, segmentation and recognition for gemstones

• Develop LLM-applications specific to gemstone domain leveraging on latest frameworks

• Conduct User requirements, scope the AI/computer-vision project and prepare documents to define nature of dataset required for machine-learning model training

• Work collaboratively with an entrepreneurial team of IOT-product engineers, machine learning & data scientist and software engineers, both in-house or Vendors, to successfully develop and deploy a cutting-edge solution

• Develop a comprehensive MLOps environment to manage the entire lifecycle and pipeline of machine learning projects, as well as maintain a well-documented code repository

• Conduct research and product development projects using internal gatekeeping process, prepare project and user requirements specifications, execute experiments and investigations, document and report findings, communicate to key stakeholders, and handover to downstream teams

• Execute the necessary data preparation & pre-processing, AI-model building, testing, validation and deployment to ensure reliable and scalable AI solution

Requirements:

• Bachelor’s or master’s degree in computer science, data science, artificial intelligence or related engineering fields.

• Minimum 3 to 5 years of proven experience in developing ML/DL architectures to solve real-world computer vision problems

• Strong proficiency in Python with hands-on experience in mainstream deep learning frameworks (PyTorch and TensorFlow) and their associated computer vision libraries (e.g., OpenCV, torchvision, timm, Hugging Face Transformers)

• Experience in computer vision with OpenCV and modern deep learning architectures, with a strong emphasis on Vision Transformer (ViT)-based models (e.g., DETR, DINOv2, SAM) and vision–language foundation models such as CLIP and its variants (SigLIP, BLIP); working knowledge of contrastive learning, self-supervised pre-training, and few-shot / zero-shot adaptation for downstream tasks including detection, segmentation, classification, and retrieval

• In-depth understanding of digital image processing, image transformation techniques, real-time image analytics and feature extraction in computer vision

• Experience in large-scale image data processing and architecting of data pipelines

• Possess data storytelling, information visualisation and technical writing skills

• Excellent research and problem-solving abilities, whilst maintaining curiosity about new things and enthusiasm to learn and share latest methods/techniques within the team

• Hands-on experience with cloud platforms (AWS, GCP) and modern backend/serving stacks (FastAPI, Redis, Docker) for end-to-end AI model development, deployment, and scalable inference

• Hands-on proficiency with modern AI coding agents (e.g., Claude Code, Cursor, GitHub Copilot), including their extensibility features such as Skills, Plugins, sub-agents and MCP integrations; strong prompt-engineering skills and the ability to leverage AI-assisted development workflows productively in day-to-day engineering tasks

• Command good communication and collaboration skills, with a strong sense of responsibility, integrity and reliability