Google cambridge office
Whether developing experiments, prototyping implementations, or designing new architectures, Research Scientists work on real-world problems in computer science. Our Research Scientists work across data mining, natural language processing, hardware and software performance analysis, improving compilation techniques for mobile platforms, core search, and much more.
Google Cambridge
To accommodate Google’s continued growth, 3 Cambridge Center, an existing four-story commercial office and retail building, was redeveloped as 325 Main, Google’s next-generation work environment in the heart of Kendall Square. The high-performance design comprises approximately 343,000 gsf (31,900 m 2 ) of innovative office space on sixteen floors as well as 42,000 gsf (3,900 m 2 ) of retail at the lower levels.
With an activated ground and second floor retail edge along Main Street and the façade abutting Kendall Plaza, 325 Main significantly enhances the pedestrian experience while enlivening the public realm. A welcoming pedestrian connection from Kendall Plaza up to the Kendall Square Rooftop Garden creates a multi-level public terrace overlooking Main Street and Kendall Plaza with potential for community programming. 325 Main further enhances neighborhood connectivity with a pedestrian connection between Pioneer Way and the Kendall Plaza. The existing MBTA headhouse serving the Kendall Red Line T-Station will be integrated at Kendall Plaza.
325 Main’s massing was conceived as a parallelogram, opening the space between the adjacent buildings and public areas. Articulating its massing, a series of inset “apertures” provide interest and balance, while creating outdoor tenant terraces. Connecting 325 Main and the 355 Main Street building, a sloped “gasket” element creates a visual distinction between them while preserving the latter’s architectural integrity. Upper floors along Main Street have been pulled away from 355 Main Street to distinguish the visual separation. A glass façade, comprising spandrel, frit and vision glass and metal panels, will articulate the building.
News
- Cambridge Day >Kendall rooftop garden to be razed for redesign, but its plants are getting out alive, with residents
- New Haven Independent >Google HQ Design Takes Shape Above Chapel St.
- Press Release >Pickard Chilton Tapped by Boston Properties to Design 325 Main, Google’s New Cambridge HQ
Cambridge
We work on fairness, interpretability and visualization of machine learning algorithms and data; new methods in machine learning and systems for machine learning research; applications of machine learning in the basic sciences; machine perception; and operations research.
Our teams in Cambridge work closely with academics at local universities as well as collaborators at local institutes with a goal to impact both Google’s products and general scientific progress. We accomplish this by releasing open source tools, publishing our work and sharing our findings with the academic community.
Research areas
Algorithms and Theory
Health and Bioscience
Human-Computer Interaction and Visualization
Machine Intelligence
Machine Perception
Speech Processing
Some of our teams
Athena
Algorithms and Optimization
Applied Science
Climate and Sustainability
Global Networking
Health
Operations Research
Perception
Responsible AI
Some of our work
Forecasting earthquake aftershock locations with AI-assisted scienceMachine learning-based forecasts may one day help deploy emergency services and inform evacuation plans for areas at risk of an aftershock.
Text Embedding Models Contain Bias. Here’s Why That Matters.Neural network models can be quite powerful, effectively helping to identify patterns and uncover structure in a variety of different tasks. At the same time, neural models (as well as other kinds of machine learning models) can contain problematic biases in many forms.
The What-If Tool: Code-Free Probing of Machine Learning ModelsThe What-If Tool is a feature of the open-source TensorBoard web application, which lets users analyze an ML model without writing code.
How we worked to make AI for everyone in 2018
Adding Diversity to Images with Open Images ExtendedAdditional imagery sets to the main Open Images dataset, to improve its diversity (geographic, cultural, demographic, subject matter, etc). Currently composed of ~478K images contributed by users of the Crowdsource app.
Work with us
Whether developing experiments, prototyping implementations, or designing new architectures, Research Scientists work on real-world problems in computer science. Our Research Scientists work across data mining, natural language processing, hardware and software performance analysis, improving compilation techniques for mobile platforms, core search, and much more.
Our research-focused software engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. From creating experiments and prototyping implementations to designing new architectures, research engineers work on machine learning, data mining, hardware and software performance analysis, improving compilers for mobile platforms and much more.
Our technical interns are key to innovation at Google and make significant contributions through applied projects and research publications. Internships take place throughout the year, and we encourage students from a range of disciplines, including CS, Electrical Engineering, Mathematics, and Physics to apply to work with us.
We believe open collaboration is essential for progress
We’re proud to work with academic and research institutions to push the boundaries of AI and computer science. Learn more about our student and faculty programs, as well as our global outreach initiatives.
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