Staff Machine Learning Engineer
PlayStation Global2 months ago
London, United KingdomStaff+
Responsibilities
- Develop and improve core generative models for graphics and video processing in applications such as live video streaming and game rendering.
- Research and prototype new methods for graphics and video enhancement.
- Build data-generation pipelines from generative models.
- Collaborate on technical publications and patent submissions.
- Participate in core R&D activities with other Sony Interactive Entertainment teams.
Requirements
- PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics, or a related field, or equivalent skills demonstrated through relevant work experience.
- At least seven years of demonstrable research experience in industry or academia.
- At least seven years of experience developing advanced applications in image, video, graphics processing, or computer vision.
- Strong experience with TensorFlow or PyTorch, Python, and packages or libraries related to computer vision or graphics.
- Evidence of leading technical developments through several publications in top-tier conferences such as CVPR, ECCV, ICCV, or SIGGRAPH.
- Experience with neural network architectures, advanced loss functions, convolutional, recurrent, transformer-based, diffusion-based, or other task-specific architectures.
- Experience training, validating, and evaluating deep neural network models on large datasets, using Python libraries such as HDF5 or similar.
- Desired experience with publications in relevant journals and conferences including IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, CVPR, ICCV, ECCV, NeurIPS, ICML, or ICLR.
- Desired theoretical understanding of graphics pipelines, coordinate transformations, PBR materials, rasterization, lighting, and ray tracing.
- Desired experience in image processing theory and practical methods.
- Some experience with 3D engines such as Unreal or Unity, including dataset generation, G-buffer extraction, and motion vectors.
Benefits
- Hybrid working within Flexmodes
- Private medical insurance
- Dental scheme
- 25 days holiday per year
- On-site gym
- Subsidised café
- Free soft drinks
- On-site bar
- Access to cycle garage and showers
- Discretionary bonus opportunity