Research Engineer, Multimodal Generative AI (Image/Video)

Research Engineer, Multimodal Generative AI (Image/Video) Seattle, WA 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 The role of the Research Engineer will be to develop state-of-the-art methods for multimodal generative AI models, with a primary focus on image generation and editing. This role is for the team behind “Nano Banana”.

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high-profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming year!

About Us

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

Research Engineers at Google DeepMind lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence. Having pioneered research in the world's leading academic and industrial labs, PhDs, post-docs, or professorships, Research Engineers join Google DeepMind to work collaboratively within and across Research fields.

They are expected to independently build state of the art foundation models and research infrastructure, work with teams on large scale AI, and develop solutions to fundamental questions in machine learning and AI. Drawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Research Engineers are at the forefront of groundbreaking research.

Key Responsibilities

Design, rapidly implement, and rigorously evaluate cutting-edge deep learning algorithms, data curation, and evaluation infrastructure for multimodal generative AI, with a particular emphasis on image synthesis. Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.

Suggest and engage in team collaborations to meet ambitious research goals, while also driving significant individual contributions. Work in collaboration with our Ethics and Governance teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

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: PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience. Proven experience in deep learning research and development, particularly in generative AI and related to image synthesis.

This includes diffusion models and autoregressive generative models. Experience with post-training is a plus.  Exceptional engineering skills in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a track record of building high-quality research prototypes and systems. Strong publication record at top-tier machine learning, computer vision, and graphics conferences (e.g., NeurIPS, ICLR, ICML, SIGGRAPH, CVPR, ICCV).

In addition, the following would be an advantage:  Demonstrated experience in multimodal generative modeling, especially combining large language models with visual generation (e.g., text-to-image/video systems, joint autoregressive and diffusion models).A keen eye for visual aesthetics and detail, coupled with a passion for creating high-quality, visually compelling generative content.

A real passion for AI!

What We Offer

At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options.

We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc. We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

The US base salary range for this full-time position is between $166,000 USD - $244,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf.

For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.      

Founded in the UK in 2010 and acquired by google in 2014, Google DeepMind aims to research and build safe artificial intelligence system to solve intelligence and advance science and humanity. An team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.

They use their technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and...