Researcher - Machine learning and Perceptual Quality

Huaweicanada; Edmonton; On-site; CAD 60,000 - 100,000; Full time

Job summary

An innovative company is seeking a Researcher to join their Software-Hardware System Optimization Lab for a 12-month contract. This role focuses on enhancing smartphone camera performance through cutting-edge AI algorithms and deep learning techniques. You'll be at the forefront of research, investigating advanced models and techniques to optimize image quality and perceptual metrics. If you're passionate about AI and eager to contribute to groundbreaking smartphone technology, this opportunity offers a dynamic environment to make a significant impact.

Qualifications

• Experience in developing deep learning algorithms for image processing.
• Strong background in AI techniques and optimization strategies.

Responsibilities

• Research and implement algorithms to enhance camera image quality.
• Design deep learning tools and workflows to improve perceptual quality.

Skills

Deep Learning

Image Quality Assessment

Reinforcement Learning

Algorithm Optimization

AI Techniques

Education

Bachelor's Degree in Computer Science or related field

Master's Degree in AI or Machine Learning

Tools

Python

TensorFlow

PyTorch

Job description

Huawei Canada - Researcher (12-Month Contract)

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

The Software-Hardware System Optimization Lab focuses on enhancing the power efficiency and performance of smartphone products through software-hardware systems optimization utilizing AI across various components. We track cutting-edge technological trends to strengthen mobile AI, camera perceptual quality, graphics, multimedia, and software architecture for mobile devices.

About the job:

1. Research and implement algorithms to improve image quality for camera products, focusing on developing and optimizing deep learning-based algorithms.
2. Research algorithms to enhance image quality, including optimization, deep learning, fine-tuning (e.g., LoRA), image quality assessment, reinforcement learning, etc.
3. Investigate foundation models (CLIP-LMMs and LLMs) and diffusion models for applications in image quality assessment (IQA) and style transfer.
4. Apply large language model soft prompting techniques to specialize in image quality assessment question answering.
5. Research areas such as color style transfer, AI white balancing, and tone mapping.
6. Design and develop deep learning tools, metrics, and workflows to improve camera perceptual quality.
7. Stay updated on recent advances in related fields and publish findings in top-tier conferences.

Note: This description consolidates repeated points and removes redundancy for clarity and conciseness. The original job posting can be found here.