Back to Job Listings

Vision AI Engineer

SpringCube

Full time - Senior Engineer

Cybersecurity

Singapore, All Areas

Published 3 weeks ago

Salary: Disclosed upon interview

Contact Employer
  • Share:
Send Feedback
Report This Job

Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading technology organization is seeking a Vision AI Engineer to advance video intelligence systems using state-of-the-art vision-language models. The company focuses on combining cutting-edge research with practical AI applications to deliver scalable, production-ready solutions for video understanding across multiple domains.

Summary
The Vision AI Engineer will design, implement, and optimize video analytics pipelines powered by modern vision-language models. The role requires hands-on expertise in deep learning, model deployment, and integrating AI solutions with production systems.

Key Responsibilities

  • Build end-to-end video analytics pipelines using vision-language models (VLMs)
  • Fine-tune and adapt foundation models for domain-specific video understanding
  • Integrate VLM reasoning with traditional video analytics components
  • Develop and maintain inference pipelines for video and multimodal data
  • Deploy and optimize models for scalable, high-performance production use
  • Diagnose model issues and enhance system stability and robustness
  • Collaborate with product and engineering teams to deliver AI-driven features

Required Qualifications

  • Strong background in computer vision, video analytics, or AI engineering
  • Practical experience with vision-language and video-language architectures
  • Hands-on experience fine-tuning, evaluating, and deploying deep learning models
  • Familiarity with foundation models such as CLIP-based architectures, BLIP/BLIP-2, and open-source VLMs (e.g., Qwen-VL, InternVL)
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch)
  • Solid understanding of CNNs, Transformers, and attention mechanisms
  • Experience with model optimization techniques (quantization, batching, memory strategies)
  • Experience deploying models on Docker, cloud platforms, or on-prem GPU systems

Preferred Qualifications

  • Master’s or PhD in Computer Vision, Machine Learning, AI, or related fields
  • Experience with real-time or near-real-time video analytics
  • Familiarity with traditional video analytics methods (detection, tracking, motion analysis)
  • Exposure to MLOps workflows (versioning, CI/CD, monitoring)
  • Interest in modern VLM and video understanding research

What We Offer

  • Opportunities to work on cutting-edge multimodal AI technologies
  • Ownership of production-scale video intelligence pipelines
  • A collaborative environment that blends research and engineering

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.