Senior Software Engineer, Google Research

Key Skills

Algorithms, Common data structures, Data structuring, Deep Learning, Large Language Models - LLMs, Natural Language Processing (NLP), TensorFlow

Job Description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 2 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, or natural language processing.
• Experience in working with large language models (LLM).

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.

Multimodal screen and UI understanding is key for assisting users with their needs to interact with devices and communicate with each other through devices. To meet these needs, we are taking a holistic approach to model the semantic and functional roles of device UI. In this role, you will help advance the state-of-the-art in multimodal screen and structured document understanding.

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.

The US base salary range for this full-time position is $157,000-$235,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Work with the project team to build and continually advance the Screen AI Foundation models and adapt them to a wide range of downstream tasks, including screen/structured document-based question answering, device screen/web page annotation, automatic navigation, captioning, adaptation, summarization, etc.

Publish technical papers in leading machine learning/AI conferences, and contribute to the scientific community.

Participate in proposing, designing, and planning of projects.

Be responsible for a combination of infrastructure building, and modeling and analysis of ScreenAI technology and datasets.

Work with cross-functional teams to accelerate and scale the development of the technology.