Research Engineer, People Identity
Mountain View, CA
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 team collaborates closely with a wide variety of teams across Google/Alphabet, leveraging Google DeepMind expertise to deploy advanced machine learning algorithms with the goal of improving Alphabet products and services.
We are a driven, collaborative, diverse team based in Mountain View, Los Angeles, New York and London. We collaborate closely within Google DeepMind, Google Research and product partner teams.
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
You’ll be applying the most promising models and research to high-impact real world problems, by rapid-prototyping initial concepts, and designing and running experiments to evaluate the opportunity. You will gain an understanding of the path from research to production whilst working on real world problems, with the chance to see your work make a difference.
Some of our current projects are focusing on multimodal human understanding and generation, including privacy preserving generation and misinformation prevention. Having relevant experience is highly beneficial. The responsibility includes model development (data, modeling and evaluation), research and prototyping.
About you
We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves prototypes forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.
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, or Machine Learning related field.Experience with people understanding/generation.Experience working with VLMs.Proven experience of ML frameworks such as TensorFlow/JAX.
In addition, the following would be an advantage:
- Experience in applying experimental ideas to applied problems
- Cross functional collaboration experience (w/ other eng/researchers)
The US base salary range for this full-time position is between $182,000 - $192,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
Top Skills
What We Do
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.
Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.
We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.
