Software Engineer, Speed, Google Research

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.
• 2 years of experience with data structures or algorithms.
• 1 year of experience with Natural Language Processing (NLP) concepts or techniques.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience developing accessible technologies.

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.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities

• Develop optimized fast inference algorithms in Google's Large Language Model (LLM) codebases.
• Improve decoding efficiency/latency and prefillI efficiency/latency.
• Analyze and profile execution via xprof and other tools.
• Develop pre-training, tail-patching and torso-patching compute-efficient and token-efficient models.
• Introduce modeling architectural changes to improve efficiency or quality. Work closely with the Gemini Development and Modeling (GDM), the Gemini team and Product Areas to address the product needs in those areas.