Research Engineer, Paradigms of Intelligence

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• One or more scientific publication submissions for conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ALIFE, GECCO etc.).

Preferred qualifications

• Experience in differentiable simulations and the intersection of deep learning with physical or biological systems (e.g., Artificial Life/ALife, morphogenesis, or dynamic texture synthesis).
• Experience developing real-time interactive systems or large-scale dataset modeling (e.g., inverse modeling of complex textures).
• Experience in mathematical foundation including Statistical Field Theory, Linear Algebra, and Stochastic Processes, evidenced by academic honors (e.g., National Olympiad medals or thesis awards).
• Proficiency in deep learning frameworks (PyTorch, JAX).

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Paradigms of Intelligence (Pi), a research team at Google, brings together an interdisciplinary group of researchers, engineers, and philosophers to explore the fundamental building blocks of intelligence and the conditions under which it can emerge. Just as intelligence arose through billions of years of evolution, we believe that embracing a bottom-up approach – while drawing on insights from the physical, biological, and social sciences – will allow us to develop more efficient, adaptable, and human AI.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.