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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 Key Responsibilities: This research engineer role focuses on inference-optimized model design for Gemini pretraining.
We are interested in predictable LLM quality with optimized architecture selection for fast inference. It involves a low-level understanding of common XLA primitives and how jax code runs on TPUs in practice.
Moreover, we heavily rely on various distillation techniques and spend time curating the right datasets for our models. The ideal candidate is willing to roll up sleeves to work across the LLM preparation stack (pretraining, finetuning, serving) to deliver strong models.
Experience in any of these is highly beneficial:
Natural Language Generation/Understanding Multimodal Understanding LLM serving Beam / Spark / Data processing 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:
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 Proven experience working with Large Language Models (LLMs) Knowledge of algorithm design Proven experience of Tensorflow or similar ML frameworks (e.g. JAX) is highly desirable Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models Experience fine-tuning large models (e.g. supervised, RLHF) Experience applying and productionizing state-of-the-art large visual, language and multimodal research Software Engineering experience and experience working on large-scale ML projects highly desirable Proven experience working in industry, working on projects from proof-of-concept through to implementation highly beneficial. A passion for Artificial Intelligence Great communication skills and proven interpersonal skills In addition, the following would be an advantage:
Experience in applying experimental ideas to applied problems Cross functional collaboration experience Prior experience collaborating with researchers Prior experience working with product teams What we offer At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc.
The US base salary range for this full-time position is between $136,000 - $300,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.
We are also open to relocating candidates to New York, NY and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).