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Vision AI Engineer

SpringCube

Full time - Senior Engineer

Cybersecurity

Singapore, All Areas

Published 3 weeks ago

Salary: Disclosed upon interview

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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.

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SpringCube is a technology recruitment firm and tech-focused career platform. Since 2001, we’ve connected top talent with leading companies across Singapore and Southeast Asia.

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