Senior Machine Learning Engineer

Role Overview:

We are looking for an independent, dedicated Senior Machine Learning Engineer to join our team and contribute to redefining the world of game play and live streaming via advanced R&D. Engage with a world-leading team of engineers and help solve some of the cutting edge problems in machine learning, video streaming and computer vision.

What you’ll be doing:

• Develop and improve core deep learning architectures 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 fast graphics or video enhancement
• Draft publications and patent submissions in collaboration with other team members
• Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment

What we’re looking for:

• 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
• 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 36 months experience)
• Strong 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 or other neural network architectures in a task-specific manner;

(iii) 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

(iv) Working experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc

Desired qualifications:

• Publications 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
• Theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
• Solid experience in image processing theory and methods, evidenced by the development of practical designs in this area
• Experience in using Docker containers or similar