Research Engineer, Gemini

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
Gemini Human Data is looking for a Research Engineer with a passion for data to join a team of researchers and engineers working on advancing the capabilities of Google’s natively multi-modal GenAI. With training data quality widely seen as key to reaching SOTA performance, we focus on developing methods for sourcing SFT and RLHF data in close collaboration with an interdisciplinary team of human-computer interaction researchers, QAs and Natural Language Processing experts. The successful candidate will help us advance our (post-)training data expertise in lockstep with the newest ML research, navigating a world of rapidly evolving models that increasingly exhibit superhuman behavior.
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.
Key responsibilities
work with an interdisciplinary team of training data experts on collecting data from human raters while defining and monitoring quality standards
use the collected data to improve model quality via supervised fine-tuning and reinforcement learning
evaluate model improvements by establishing appropriate metrics, running experiments and evaluations, and eyeballing test data
understand interactions and dependencies between different aspects of model quality: truthfulness/factuality, style, modality/format, safety
make calls with regard to non-trivial metrics tradeoffs
Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
Requirements
Masters degree or equivalent in an ML-related topic
hands-on experience with training Large Language Models or Generative AI
proficiency in Python, C++ or equivalent programming languages
experience with and interest in data-driven quality work.
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:
see the requirements section above.
In addition, the following would be an advantage:
hands-on experience with LLM/GenAI-based products, understanding user behavior, logs analysis
background in Natural Language Processing
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