Senior Staff Research Engineer

• Develop innovative machine learning and natural language processing techniques in the directions that are of high impact to the organization, push important scenarios, and 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 at scale across various real-world AI issues of enterprises.
• Engage with and learn from researchers and engineers across Google.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with design and architecture; and testing/launching software products.
  
• 5 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI - related concepts (e.g., language modeling, computer vision).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures/algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience with publications in related research venues (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR, etc).

Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.

As a part of the Google Cloud AI Research team, you will address high-impact AI research issues driven by Google Cloud's mission of bringing AI to tech, healthcare, finance, retail and many other industries. You will work on a range of unique problems focused on maximizing both scientific and real-world impact, advancing AI across venues while collaborating with teams to bring innovations to production.

In this role, your work will involve improving foundation models to solve issues like hallucinations and generalization, retrieval-augmented LLMs and LLM-assisted search and pushing the boundaries of GenAI 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with design and architecture; and testing/launching software products.
  
• 5 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI - related concepts (e.g., language modeling, computer vision).