Video/Image AI/ML Software Engineer Graduate (Multimedia) - 2027 Start (PhD)

About the team Our team is building industry leading, highly efficient and scalable video codec hardware solutions (FPGA and ASIC) from the ground up to better serve our billions of users.

We are looking for strong software and firmware engineers to design algorithms, C-model, and firmware for advanced video encoding and processing implemented in dedicated hardware accelerators.

The successful candidate will be part of a fast growing team that includes algorithm, architecture, software, firmware, and hardware design and verification experts with a dedication to technical excellence and a passion to build large-scale and high-performing video platforms and services.

We are looking for talented individuals to join our team.

As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year.

Please state your availability and graduation date clearly in your resume.

Responsibilities: - Design video analysis (ROI, content understanding, feature extraction etc.) and quality assessment algorithms, and participate in database creation, algorithm design/development/optimization, etc. - Participate in designing strategy and solutions for E2E video quality optimization with a combination of video analysis, processing and encoding algorithms, such as frame-level rate control. - Apply designed algorithms for VOD / Live streaming monitoring, data analysis, objective evaluation for algorithms etc. - Collaborate with Infra and multi-media platform teams to integrate algorithms into production workflows and validate their impact through A/B testing.

Minimum Qualifications: - Individuals who are completing or have recently completed a PhD degree in computer science, electrical engineering, mathematics, statistics or a related discipline. - Excellent programming, debugging, and optimization skills in one or more general-purpose programming languages, including but not limited to: C/C++, Python - knowledge of image/video analysis algorithms or subjective/objective image/video quality algorithms, and state-of-the-art technologies, such as VMAF, PSNR and SSIM and etc.

Preferred Qualifications: - Familiar with Transformer architectures and mainstream multi-modal large models (MLLMs), and hands-on implementation or research experience preferred. - Knowledge of common video processing algorithms, such as supperresolution, defusion model, etc. - Experience of machine learning or deep learning and familiar with deep learning frameworks (Tensorflow/Pytorch) - Knowledge of video codecs (AVC, HEVC, AV1, VP9, etc.) and experience in video codec design - Experience with embedded processors like ARM Cortex M0/M3/M4 or RISC-V architecture and real-time development on RTOS environment. - Great communication, eager to learn, and always passionate about turning cutting-edge technologies into real life use cases.