jobs in A*STAR - Agency For Science, Technology And Research

全职 Lead Research Engineer, Aural - Language Intelligence, I2R 工作, 薪水, A*STAR - Agency For Science, Technology And Research 公司招聘中 - Ricebowl

Lead Research Engineer, Aural - Language Intelligence, I2R

A*STAR - Agency For Science, Technology And Research

Undisclosed

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

Job Summary

Join Us in Shaping the Future of Audio Intelligence

We are excited to embark on the next phase of MERaLiON, pushing the boundaries of audio understanding beyond traditional speech processing. Our mission is to unlock rich, real-world audio signals—enabling machines to interpret, reason, and respond to sound in ways that were previously unimaginable.

We are seeking passionate R&D Engineers / Scientists to join our team in building next-generation, intelligent, real-time multimodal large language model. These innovations will power transformative applications in digital services, transportation, manufacturing, healthcare, finances and beyond.

Responsibilities

  • Design and build advanced models that understand, generate, and reason over complex audio inputs.
  • Engineer low-latency, scalable solutions for real-world deployment, delivering seamless user experiences at production scale.
  • Apply Gen AI, Deep Learning and able to use AI assisted coding in data engineering, ML engineering, to create robust data pipelines, training frameworks and prototypes in fast turnaround time
  • Use system-level thinking, stay at the forefront of state-of-the-art research, and translate novel ideas into impactful systems, prototypes, and products.
  • Rapidly prototype and iterate, showcasing new capabilities and accelerating technology transfer.

We are looking for engineers and researchers who have strong computer science fundamentals with a builder’s mindset.

Requirements

  • Strong programming and engineering skills (Python/PyTorch, C/C++, or similar)
  • Solid grounding in computer science, machine learning, and deep learning
  • Experience with DevOps and MLOps, including model training, deployment, and monitoring
  • A passion for Applied AI engineering, with the ability to move quickly from ideas to working systems
  • Curiosity about productivity tools and workflows that accelerate development and experimentation

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