jobs in PANASONIC R&D CENTER SINGAPORE

全职 R-D Engineer (Computer Vision - Generative AI) 工作, 薪水 up to SGD 1, PANASONIC R&D CENTER SINGAPORE East Region (Singapore) 公司招聘中 - Ricebowl

R-D Engineer (Computer Vision - Generative AI)

PANASONIC R&D CENTER SINGAPORE

每月

East Region (Singapore)

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工作地点

  • 202 BEDOK SOUTH AVENUE 1 East Region (Singapore) Singapore

职位描述

岗位职责

Responsibilities:

1)    Research, design, and develop computer vision and deep learning models for image and video understanding.

2)    Work on Generative AI systems, including:

a.    Large Language Models (LLMs)

b.    Vision-Language Models (VLMs)

c.     Multimodal and generative architectures.

3)    Develop and own the full AI lifecycle:

a.    Data preparation and experimentation

b.    Model training and fine-tuning

c.     Evaluation, optimization, and benchmarking

d.    Deployment to local, edge, or cloud environments.

4)    Collaborate with cross-functional teams and clearly communicate progress and results.

Requirements:

1)    Degree in Electronic/Computer Engineering/Computer Science/AI or related discipline

2)    Strong foundation in Computer Vision and Deep Learning.

3)    Hands-on experience with Generative AI, including LLMs, VLMs, or related multimodal models.

4)    Experience in:

a.    Model training and fine-tuning with real-world datasets

b.    Deployment and inference optimization

5)    Strong programming skills in Python, C++

6)    Solid understanding of software engineering principles and application development.

7)    Ability to work independently, manage projects end-to-end, and learn new technologies quickly.

8)    Strong problem-solving, communication, and teamwork skills.

Preferred / Added Advantages:

- Experience with Pytorch / TensorFlow, OpenCV, Hugging Face ecosystem.

- Exposure to Video models, Temporal modelling, or Multimodal transformers.

- Experience with cloud, edge, or on-device deployment.

- Familiarity with Docker, REST APIs, FastAPI/Flask, or similar frameworks.

- Prior experience with:

o   Publications (journals, conferences)

o   AI competitions (e.g., Kaggle, CV challenges)

o   Open-source contributions or research prototypes.

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