Google

Research Engineer focused on inference-optimized model design for Gemini pretraining, working across the LLM preparation stack (pretraining, fine tuning, serving) and understanding JAX/TPU execution. Requires 5 years of experience in inference-optimized model design and experience with product teams.

Research Scientist role focused on developing new algorithms in AI for mathematics and theoretical research, with a focus on privacy and machine learning, and translating these insights into Google products. The role involves publishing research in top conferences.

Research Engineer at Google DeepMind focused on architecting, scaling, and landing latent thinking in Large Language Models (LLMs) and reasoning. The role involves developing novel algorithms, formulating research hypotheses, designing and implementing ML experiments, and partnering with teams to integrate scientific breakthroughs into frontier models. Experience in LLM training (pre-training or post-training) and publishing research is preferred.

Staff AI Research Engineer focused on architecting the strategy and roadmap for foundation recommender model pre-training. This role involves owning the research agenda, defining and prioritizing experiments for model quality under compute constraints, and partnering with data, ML infrastructure, and engagement teams to shape roadmaps, define training framework requirements, and establish evaluation benchmarks.

Research Scientist role focused on fundamental AI research, developing new products, and contributing to the research community. The role involves defining research strategies, designing experiments, and publishing findings, with a focus on machine learning and deep learning.

Staff Research Scientist at Google Cloud AI Research focusing on fundamental AI research, pushing the state-of-the-art, and collaborating with product teams to bring innovations to market. The role involves authoring research papers, defining research strategies, and contributing to the wider research community.

Senior Staff Research Scientist at Google Cloud AI Research focusing on fundamental research, new product innovation, and infrastructure goals within AI and Infrastructure. The role involves setting up large-scale tests, deploying ideas, managing deadlines, and applying theories to develop new products and technologies. It also includes contributing to the research community through publications and collaborations. The team works on hyperscale computing, AI models, and infrastructure at a global scale, contributing to products like Vertex AI. Responsibilities include authoring research papers, contributing to research growth, delivering full projects, identifying new research areas, and engaging stakeholders to address undefined problems.

Senior Software Engineer on the RecML team, focused on scaling machine learning for recommendations and user modeling. The role involves architecting and implementing model-parallel training, optimizing transformer models, and writing low-level code for performance. This is a horizontal ML infra and efficiency role supporting the training framework of foundation recommender models.

Research Scientist at Google Research focusing on fundamental research and innovation in AI/ML, contributing to intelligent systems for Google products. Responsibilities include authoring research papers, defining research solutions, conducting experiments, and developing research prototypes. Requires a PhD and publication record, with preferred experience in owning research agendas.

Student Researcher (PhD) position at Google, focusing on exploratory research projects to advance scientific understanding and develop next-generation intelligent systems. The role involves participating in research to solve real-world, large-scale problems, with opportunities across various Google research teams.

Student Researcher Program at Google focusing on academic collaborations and scientific advancement in AI and other research areas. Students will work on exploratory projects to develop solutions for real-world, large-scale problems, potentially contributing to next-generation intelligent systems.