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Open nowPosted today

Physical AI (Edge Intelligence) Research Scientist

STARRY RECRUITMENT PTE. LTD.

Pay
SGD 7,000 – SGD 12,000 a month
Where
Central, Singapore
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Your applicationOpen nowPhysical AI (Edge Intelligence) Research ScientistSTARRY RECRUITMENT PTE. LTD. · Central, Singapore

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Share of postings closed within
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  2. 4.5%3 days
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  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted today

The posting

Key Responsibilities

  • Conduct research on Physical AI, Embodied AI, Multimodal AI, and Foundation Models for real-world applications.
  • Develop and fine-tune Vision-Language Models (VLMs), Vision-Language-Action (VLA) models, multimodal models, and action-generation policies for physical systems.
  • Design and implement AI algorithms for perception, reasoning, decision-making, and action generation using multimodal sensory inputs.
  • Optimise AI models for efficient edge inference, including model compression, quantisation, pruning, knowledge distillation, and computational graph optimisation.
  • Deploy and benchmark AI models on edge computing platforms and physical testbeds, integrating camera feeds and other sensor inputs.
  • Use simulation environments for synthetic data generation, model pre-training, domain adaptation, and sim-to-real evaluation.
  • Work with hardware acceleration engineers to optimise AI workloads for target edge platforms and achieve low-latency, real-time inference.
  • Develop AI inference pipelines using frameworks and tools such as PyTorch, ONNX, TensorRT, and related deployment technologies.
  • Conduct experiments, benchmark model performance, analyse results, and translate research ideas into working prototypes.
  • Publish research findings in leading AI/ML, computer vision, robotics, or related conferences and journals.
  • Identify opportunities for technical patents and intellectual property arising from research and engineering work.

Qualifications

  • Ph.D. in Computer Science, Artificial Intelligence, Computer Vision, Robotics, Electrical Engineering, or a related quantitative discipline. Exceptional candidates with a research-oriented Master's degree and strong publications may also be considered.
  • Strong research background in one or more of the following:
  • Physical AI / Embodied AI
  • Multimodal AI
  • Vision-Language Models (VLMs)
  • Vision-Language-Action (VLA) Models
  • Foundation Models
  • Computer Vision
  • Robotics / Robot Learning
  • Edge AI
  • Strong understanding of Deep Learning, Transformers, multimodal models, or generative AI.
  • Strong publication record in top-tier AI/ML, computer vision, robotics, or related conferences and journals.
  • Strong proficiency in Python and PyTorch.
  • Familiarity with AI model deployment and optimisation frameworks such as ONNX, TensorRT, or similar inference frameworks.
  • Experience with model compression, quantisation, pruning, knowledge distillation, or inference optimisation is highly desirable.
  • Experience deploying AI models on edge devices, embedded platforms, robots, or physical testbeds is highly desirable.
  • Working knowledge of C/C++ is preferred.
  • Strong research, experimentation, analytical, and scientific communication skills.

Preferred Research Experience

Candidates with experience in any of the following areas are particularly encouraged to apply:

Physical AI / Embodied AI | Robotics | VLM / VLA | Multimodal Foundation Models | Computer Vision | Edge AI | Model Optimisation | Sim-to-Real | Robot Learning | Real-Time AI Inference

What You Will Work On

The research pipeline will typically span:

Foundation Models → Multimodal Perception & Reasoning → Action Generation → Model Optimisation → Edge Deployment → Physical Testbed Validation

The role is primarily focused on AI algorithms, model research, optimisation, and edge deployment, rather than semiconductor IC design or hardware architecture development.

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