Generative AI Research Engineer — Real-Time Video

WeAreTechWomen

United Kingdom

On-site

GBP 90,000 - 170,000

Full time

4 days ago
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Job summary

Google DeepMind is seeking a Research Engineer with a proven track record of building and shipping generative models in the real world. In this role, you will have strong engineering background in building, testing and deploying diffusion models applied to real-time video generation.

You will work with our modeling, data and eval teams to integrate and scale up model capabilities. You will drive cross-functional collaboration to establish rapid, iterative feedback loops spanning experiments,

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience developing, training, and deploying diffusion models and generative video architectures.
  • Experience writing custom GPU/TPU kernels for model serving (e.g., JAX or PyTorch).

Responsibilities

  • Architect and implement next-generation model architectures in collaboration with research teams to advance frontier world models.
  • Design and iterate on real-world evaluation pipelines to systematically measure and accelerate model capabilities.
  • Engineer high-performance model distillation and optimization techniques to support real-time serving at global scale.
  • Build scalable data ingestion pipelines and automated filtering mechanisms to maximize training quality.

Skills

Diffusion models
Generative video architectures
Custom GPU/TPU kernels
JAX
PyTorch

Education

Bachelor’s degree or equivalent practical experience
PhD in Computer Science / ML / AI or related field

Tools

JAX
PyTorch

Job description

Google DeepMind is seeking a Research Engineer with a proven track record of building and shipping generative models in the real world. In this role, you will have strong engineering background in building, testing and deploying diffusion models applied to real-time video generation.

You will work with our modeling, data and eval teams to integrate and scale up model capabilities. You will drive cross-functional collaboration to establish rapid, iterative feedback loops spanning experiments,

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