Staff Machine Learning Engineer
Salary not listed • United Kingdom, London • Full-time
Posted 2mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Sony Interactive Entertainment (SIE) is seeking a Staff Machine Learning Engineer to join the Visual Computing Group (VCG). This role will focus on advanced R&D to redefine game play and live streaming through cutting-edge neural networks and ML. The VCG team aims to design and deploy systems that push the boundaries of runtime efficiency, visual quality, and latency in game rendering and streaming.
Responsibilities
- Develop and improve core generative models for graphics and video processing for applications like live video streaming and game rendering.
- Research and prototype new methods for graphics or video enhancement and data generation pipelines using generative models.
- Collaborate with team members on drafting publications and patent submissions.
- Participate and assist in core R&D work with other teams within Sony Interactive Entertainment.
Requirements
- PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics, or a related field, or equivalent work experience.
- 7+ years of demonstrable research experience in industry or academia.
- Strong background in TensorFlow or PyTorch, Python, and computer vision or graphics libraries.
- Experience developing advanced applications in image/video/graphics processing or computer vision (minimum 7 years).
- Evidence of leading technical developments through publications in top-tier conferences (e.g., CVPR, ECCV, ICCV, SIGGRAPH).
- Solid background in neural network architectures, including formulating and testing advanced loss functions.
- Experience designing and testing advanced neural network architectures (convolutional, recurrent, transformer-based, diffusion-based) for specific tasks.
- Experience in training, validation, and evaluation of deep neural network models on large datasets using Python libraries like HDF5.
Benefits
- Discretionary bonus opportunity
- 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