Research Engineer, AI/Machine Learning

Minimum Qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, and with data structures or algorithms.
• 2 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning or natural language processing.
• Experience with Large Language Models, NLP, or Generative AI.
• Experience conducting research and publishing results in relevant fields (e.g., conference publications, journal articles, preprints).

Preferred Qualifications:

• PhD in Computer Science.
• Experience developing accessible technologies.
• Experience with applying ML/AI research to real-world problems and demonstrating impact.
• Experience with emerging AI research areas (e.g., multi-agent systems, prompt engineering).

About the job
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

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.

Responsibilities

• Conduct research on emerging AI topics such as multi-agent systems, prompt engineering, model optimization, and other areas identified in collaboration with Google Research and DeepMind organizations.
• Develop and evaluate novel ML models and techniques for pilot projects, rapidly iterating to demonstrate feasibility and potential impact. Translate successful prototypes into scalable solutions.
• Work closely with researchers, engineers in Mountain View, and product teams across Google to identify and address AI challenges in various domains.
• Contribute to the technical direction of the team and participate in the broader ML research community. Share expertise and insights gained from applied research and pilot engagements.
• Publish research findings in venues and share insights with the wider ML community. Contribute to internal knowledge repositories and documentation to facilitate the adoption of new techniques and tools.