About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

In this role, you will join a great team of research scientists and engineers that are addressing high-impact real world problems for Google Cloud to help AI transform the world!

The Google Cloud AI Research team addresses AI research challenges motivated by Google Cloud’s mission of bringing AI to technology, healthcare, finance, retail and many other industries. We work on a range of unique high-impact problems with the goal of maximizing both scientific and real-world impact both pushing the AI in top venues and collaborating across teams to bring innovations to production. The example directions include: improving foundation models to solve issues like hallucinations and generalization, retrieval-augmented LLMs and LLM-assisted search, and pushing the boundaries of Generative AI for multimodal inputs and outputs.The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Develop innovative machine learning and natural language processing techniques in the directions that are of high impact to the organization, publish outcomes at conferences and journals.

• Collaborate with Google Cloud product teams to address customer needs and realize the business impact of research breakthroughs via Google Cloud AI products.

• Invent and implement generalizable methods that perform across various real-world AI issues of enterprises.

• Engage with and learn from talented researchers and engineers across Google.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience with software development in one or more programming languages.

• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

• 1 year of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications

• Master's degree or PhD in Computer Science or related technical field.

• 5 years of experience with data structures and algorithms.

• 1 year of experience in a technical leadership role.

• Experience developing accessible technologies.