Research Engineer, Geospatial AI

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.

About Us

Our geospatial AI team works to push the state of the art in geospatial intelligence with an emphasis on sustainability applications. We work closely with high impact partners and teams across Google to deliver solutions that transform Google's interface to the real world and tackle some of the biggest challenges facing the future of our planet.

We are an agile, collaborative, and specialised team based in London and New York. We build end-to-end systems spanning the machine learning life cycle, typically in close collaboration with each other to execute towards a shared vision. Our team prioritises quality and usability for everyone, with a consistent focus on positive societal outcomes.

The Role

Key responsibilities:

You'll be developing the next frontier of models for geospatial understanding. Your work will include the implementation of production ready systems, and experimentation / hypothesis testing to evaluate improvements and new opportunities. You will be part of a tight knit team with a short path to impact for major sustainability initiatives and user facing interfaces. Your job responsibilities will shift with the team as phases of the project develop, from prototypes to engineering milestones to production.

Your role will require problem solving and novel research in one of the most challenging data domains. We are highly collaborative, so expect to work frequently with core and extended team members across Mountain View, New York, and London.

About You

We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves the project 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 working on our geospatial AI team, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry
• Proven knowledge and experience of Python or C++
• Knowledge of machine learning and statistics 
• Knowledge of algorithm design
• Proven experience with ML frameworks (e.g. JAX) is highly desirable
• Background in ecology, earth science, biogeochemistry, earth observation, or related fields is highly desirable
• Proven experience with large multimodal model training is highly desirable 

• Proven experience working in industry, working on projects from proof-of-concept through to implementation is highly desirable.
• A good understanding of computer vision research literature and models is highly desirable.
• A passion for AI
• Great communication skills and strong interpersonal skills

In addition, the following would be an advantage:

• Experience in applying experimental ideas to applied problems
• Cross functional collaboration experience
• Prior experience working with product teams

Applications close on Wednesday 9th October 2024.