Snabbfakta

    • Cambridge

Ansök senast: 2024-12-09

AI Researcher -Image Quality Metrics -Contractor

Publicerad 2024-10-10

AI Researcher


Job Purpose:

1. Be responsible for researching Image and Video Quality Metrics solutions targeted for real-time mobile game rendering.

2. Integrate AI algorithms targeted for enhancing Computer Graphics pipeline both in efficiency and quality.


Key Responsibilities:

1. Research and develop new Image and Video Quality Metrics for different types of game graphics distortions.

2. Researching, designing and developing comparison studies between Full-Reference vs Non-Reference vs Partial-Reference metric methods.

3. Tackling technical challenges and reshaping AI research solutions to become product compatible solutions.

4. Identify new AI technologies and plan for future projects and product solutions.

5. Contribute to project requirements and understand AI product deployment tradeoffs.

6. Establishing and creating datasets that meet product deployment scenarios.

7. Assess our algorithm solution robustness under different deployment scenarios.

8. Analyse and improve efficiency and performance of solutions for either cloud or on-device deployment.

9. Documenting and reporting progress to your team/senior management and to cross-location/functional teams.

10. Collaborate with cross-functional/location managers, researchers and engineers.


Person Specification:

List details of Knowledge, Skills, Experience and Qualifications needed to do the job:

Required:

• Master/PhD degree in Machine Learning/Computer science/computer vision or related technical domain.

• 4+ years of industry experience working on projects in: computer vision, image and video quality metrics, deep learning, machine learning, graphics.

• Expertise in AI, Machine Learning and Deep Learning

• Experience developing systems for manipulating image/video and multi-modality content.

• Experience in collecting, cleaning and creating datasets for AI model development.

• Minimum 5+ years’ experience in at least one of the deep learning frameworks (e.g., Tensorflow, Caffe2, Pytorch, MxNet, Torch, etc.).

• Record of publications in top-tier conferences: CVPR, ECCV/ICCV, SIGGRAPH, BMVC, NeurIPS, ICML, ICLR.


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