Role Description:
We are looking for an independent, dedicated Machine Learning Engineer/Senior ML Engineer to join the Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG’s mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency.
What you’ll be doing:
- Develop and improve core generative models for graphics and video processing for a variety of applications, such as live video streaming, game rendering, etc.
- Research and prototyping of new methods for graphics or video enhancement, and data generation pipelines from generative models
- Collaborate with team members on drafting publications and patent submissions
- Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment
What we’re looking for:
- PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
- 3+ years of experience in demonstrable research experience in industry or academia.
- Strong background in:
- TensorFlow or PyTorch;
- Python and packages/libraries related to computer vision or graphics;
- evidenced by the development of advanced applications in image/video/graphics processing or computer vision (minimum of 3 years of experience for ML engineer, minimum 5 years for Senior ML engineer)
- Evidence of leading technical developments by at least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar
- Solid background in one or more of the following:
- (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design;
- (ii) design and test of advanced convolutional, recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner;
- (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar
Desired qualifications:
- Publications, e.g. in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
- Some theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
- Experience in image processing theory and methods, evidenced by the development of practical designs in this area
- Some experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc.