Machine Learning Engineer

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.

• 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

• 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:
  • Tensor Flow or Py Torch ;
  • 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

• 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, P  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.