Senior Research Engineer, Applied Language

At 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 DeepMind Applied Language team is working on productionizing latest language ML research in real-world problems. Our vision is to build efficient and controllable language models that interact with humans and external knowledge sources. We collaborate closely with DeepMind research and multiple Alphabet teams.

The role

We look for candidates who are passionate about solving real-world problems with the latest research in natural language generation and understanding. We work with product teams to understand their objectives, product requirements, constraints, key metrics. We work with research teams to understand whether and how to apply latest research to real-world problems. We propose, build, evaluate and debug ML models and algorithms; we integrate our pipelines, models and predictions into production serving systems.

Previous experience with language models is highly preferred.

About you

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

• MSc/PhD degree in computer science, mathematics, applied stats, machine learning or similar OR BSc and several years proven experience in an applied ML role
• Experience in ML engineering and frameworks.
• Strong track record of engineering and working with complex systems and codebases.
• Experience in language models and language research.

In addition, the following would be an advantage: 

• Experience in driving a project from an experimental idea to a proof-of-concept to a launched product feature.
• Experience in cross functional collaboration, with research teams and product teams.