Research Engineer, Multimodal and Video Modeling

Google DeepMind; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading artificial intelligence firm in London is seeking a Research Engineer to develop and improve large-scale multimodal models, particularly focusing on video modeling. The ideal candidate will hold a degree in computer science or a related field and possess strong programming and engineering skills. Experience with machine learning experimentation and proficiency in major ML frameworks such as TensorFlow and PyTorch is essential. Join a talented team working to advance AI for public benefit and scientific discovery.

Qualifications

• Strong background in deep learning with relevant architectures experience.
• Experience with training large-scale machine learning models in multimodal domain.
• Excellent software engineering skills to build robust systems.

Responsibilities

• Develop and improve large-scale multimodal models with a focus on video modeling.
• Design methods for evaluating and improving multimodal generative models.
• Build data pipelines for processing large datasets.

Skills

Programming skills

Deep learning

Data processing

Software engineering

Machine learning

Education

BSc, MSc or PhD/DPhil in computer science, physics, mathematics, or equivalent

Tools

JAX

TensorFlow

PyTorch

NumPy

Pandas

Job description

Research Engineer, Multimodal and Video Modeling

London, UK

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

We’re looking for a Research Engineer with exceptional programming and engineering skills, a deep understanding of large-scale neural network training and data processing, and a strong working knowledge of machine learning experimentation. The ideal candidate will have hands‑on experience with training and developing multimodal models.

Key responsibilities:

• Develop, maintain, and improve large-scale multimodal models, with a focus on video modeling, and the data pipelines for training and evaluation.
• Design and implement novel methods for evaluating and improving multi‑modal generative models, particularly at the post‑training stage.
• Build and maintain robust data pipelines for collecting and processing large-scale datasets, including human‑labeled data.
• Collaborate with research scientists to translate research ideas into production‑ready code.

About You

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, physics, mathematics, applied statistics, machine learning, or equivalent practical experience.
• Strong background in deep learning, with proven experience with relevant architectures (e.g., Transformers, GNNs, etc).
• Experience with training large-scale machine learning models, particularly in the multimodal domain (video, text).
• Excellent software engineering skills with a proven ability to build robust and scalable systems.
• Proficiency with ML and scientific libraries such as JAX, TensorFlow, PyTorch, NumPy, and Pandas.
• Experience with either large-scale data processing frameworks (e.g., Apache Beam, Spark) or distributed training infrastructure.

In addition, the following would be an advantage:

• Experience with LLMs, VLMs, and/or diffusion models training and inference.
• Experience with Computer Vision tasks (video classification, object tracking, depth estimation etc.)
• Experience working in a team on projects from the initial proof‑of‑concept stage to final implementation and evaluation.