ASUS AICS - Machine Learning Engineer

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ASUS Global Pte Ltd
Singapore
SGD 125,000 - 150,000
Be among the first applicants.
5 days ago
Job description

About ASUS

AICS is part of ASUS, a multinational company known for the world’s best motherboards, PCs, monitors, graphics cards and routers. Along with an expanding range of superior gaming, content-creation andAIoTsolutions, ASUS leads the industry through cutting-edge design and innovations made to create the most ubiquitous, intelligent, heartfelt and joyful smart life for everyone. With a global workforce that includes more than 5,000 R&D professionals, ASUS is driven to become the world’s most admired innovative leading technology enterprise.

About AICS

The mission of ASUS Intelligent Cloud Services (AICS) is to build revolutionary healthcare solutions with natural language processing, computer vision, and big data analytics. We provide Software as a Service (SaaS) applications to accelerate the effective use of medical data and improve the efficiency of hospital operations, unleashing the power of data for precision healthcare and bringing transformative impact to the industry.

Job Responsibilities:

  • Research and implement appropriate ML algorithms and tools with a focus on optimizing performance and efficiency in maintenance.
  • Explore cutting-edge GenAI technology to integrate SOTA methodologies into our practice.
  • Work closely with an entrepreneurial team of experienced researchers and software engineers to successfully integrate ML models to production and continue to grow our business.

Requirements:

  • Bachelor’s degree or above in computer science or related field with relevant experience
  • 3+ years of experience with developing machine learning models at scale
  • Proven experience in NLP or CV projects, like multi-label classification, text summarization, motion detection and object recognition
  • Proven experience in LLM/VLM project, hands-on experience with pretrain and instruction finetune.
  • Strong programming in Python,experience with ML frameworks and libraries such as TensorFlow, PyTorch and Transformers.
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