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.

Our team is responsible for integrating diverse viewpoints and values into ground-breaking technologies like Large Language Models (VOICES of all in AI alignment).

As a Research Engineer, you will design, implement, and empirically validate fair, democratic, and inclusive approaches to alignment and harm mitigation, and integrate successful approaches into our best AI systems.

Our interdisciplinary team drives the responsible development of safe and equitable AI systems, including identifying potential harms from current and future AI systems, and conducting (socio)technical research to mitigate them.

Research Engineers spearhead innovative technical approaches, collaborating closely with internal AI research teams (like Scalable Alignment and Ethics Research), product teams (including Bard and Gemini), and external research partners.

Key responsibilities:

• Develop and implement technical approaches for integrating diverse viewpoints and values. Approaches include fair, democratic, & inclusive algorithms, scalable evaluations and oversight, and more, in coordination with the team’s broader technical agenda.
• Identify, investigate and mitigate possible risks and harms of foundation models, stemming from capabilities, human-AI interaction and systemic impacts.
• Build infrastructure that accelerates research velocity by enabling fast experimentation on foundation models (text and multimodal), and easy logging and analysis of experimental results.
• Support human data collection and data set creation.
• Collaborate with other internal teams to ensure that Google DeepMind AI systems and products (e.g. Gemini) are informed by and adhere to the most advanced safety research and protocol
• Help make sure our AI models work well for everyone.

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

• You have at least one year of hands-on experience working with deep learning and/or foundation models
• You are adept at building codebases that support machine learning at scale. You are familiar with ML / scientific libraries (e.g. JAX, TensorFlow, PyTorch, Numpy, Pandas), distributed computation, and large scale system design.
• Your knowledge of statistics and machine learning concepts enables you to understand research papers in the field.
• You are keen to address harms from foundation models, and plan for your research to impact production systems on a timescale between “immediately” and “a few years”.
• You are excited to work with strong contributors from different fields of research to make progress towards a shared adventurous goal.
• You have experience in and enjoy working as part of interdisciplinary teams.
• You have experience as tech lead on research projects
• You have an ambition to grow and lead a team of Research Engineers

• You have technical experience in responsible AI, sociotechnical AI and/or AI Safety (whether from industry, academia, coursework, or personal projects).
• You have experience in running evaluations and/or collecting human data.
• You have an interest in Natural Language Processing and related areas.
• You have experience in contributing to publishing research papers at conferences, ranging from ACL, NeuIPS, ICML, to ACM CHI, or FAccT.

Applications close on Monday 12th February 2024.