Viraj Chatterjee
Bellevue, Washington, United States
13K followers
500+ connections
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As a seasoned technology executive with extensive experience spanning multiple decades, I…
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13K followers
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Viraj Chatterjee shared thisEvery great athlete has a locker. Remember, so do you. As a football fan (I refuse to call it soccer!), I can barely contain my excitement for this summer. This is the kind of event that rearranges your whole life for a few weeks. Fellow football fans, sound familiar? Fans will be on the move: traveling to matches, gathering with friends and family, and running on schedules where flexibility is everything. That's where Amazon pickup comes in. Customers can grab their packages on their schedule, at a convenient location near the action. During one of the biggest sporting events on the planet, convenience shouldn't take a timeout. No extra time needed. Just pick up and go. 📦 Find a pickup location near you: https://www.amazon.com/ulp Ignacio López Silva, Maite Pena-Alcaraz, Michelle Kreitz, Bibiana Uribe
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Viraj Chatterjee shared thisWe’re very excited about expanding our operations in Brazil. Amazon’s investments in the country continue to speed up delivery and improve the shopping experience for customers nationwide, with Hub Delivery acceleration serving as a key enabler of this vision. I'm happy to share Núbia's testimonial, a beauty supplier and entrepreneur who delivers Amazon packages in her neighborhood during her free time. I had the privilege to meet her recently. Not only is she a great partner delivering smiles for our customers, but also a great ambassador for the program. Núbia represents thousands of local entrepreneurs across Brazil who are building their own businesses while helping us bring faster, more convenient delivery to their communities. Her story exemplifies the innovative spirit driving our Hub Delivery program forward. Watch her inspiring journey in the video below. 🎬 Learn more about Amazon's impact in Brazil on the AboutAmazon blog: https://lnkd.in/gdAjAFv6 #AmazonBrazil #HubDelivery #LocalEntrepreneurs #Innovation Awanish Narain Singh, Ricardo Pagani, Marcio Neves (He/His/Him), Rafael Caldas, Charles Burch, Praveen K, Felipe Ferreira, Luiza Granero, Thomas Kampel, Bruno A., Stu Jackson
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Viraj Chatterjee shared thisFrom time to time, I post about how we're using technology to solve some really hard problems in logistics. Today, let me share a bit about one of the most frustrating parts of a delivery driver's day: figuring out where to park. Know that feeling when you are circling around your destination downtown but can’t find parking? It’s frustrating and time-consuming. While we can’t create parking spots, we can make it easier for drivers to find them. The first challenge is simply measuring parking difficulty. Typically, the industry approach involves analyzing the difference between actual trip time and planned time near the destination, then aggregating these measurements at the street level. Because parking outcomes depend heavily on luck, sufficient observations and median values help produce stable estimates. But even with that, a big problem remains: many streets have little or no data. And more importantly, parking behavior varies from block to block. This challenge is what inspired us to build PaSTNet (Parking Search Time Model). PaSTNet is a multi-modal AI model designed to tackle this complexity. It leverages advances in graph neural networks, attention mechanisms, and pre-trained foundation models, bringing together multiple sources of information including GPS signals like circling distance and dwell time, road network features, and semantic context from satellite imagery such as curbside layouts and land-use patterns to understand parking behavior across the city. By learning how conditions vary across connected streets, this AI model can estimate parking search time even in areas with limited data. In practice, PaSTNet guides drivers to streets with easier parking including determining where to park in dense downtown areas. Kudos to our inventors! Amber Roy Chowdhury, Zhiyan Yi, George Forman, Gil Wolff
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Viraj Chatterjee shared thisReceving a package delivery shouldn't mean rearranging your entire day. That's why Amazon is partnering with Citibox, Europe's largest residential locker network, to bring secure package lockers directly to apartment buildings across Europe, where nearly half of Europeans live. Through this partnership, Amazon customers get 24/7 access to collect packages from lockers in their building lobbies whenever works best for them—early morning before work, late evening after dinner, or anytime in between. This expansion is part of Amazon's commitment to meet customers where they are. By bringing delivery options directly into residential buildings, we're adding more convenience and choice for how customers receive their orders. For delivery drivers, a single delivery point per building means safer, more efficient deliveries with fewer stairs to navigate. We're starting in Spain and expanding across the EU, bringing more flexibility to customers in the places they call home. Pictured: Sergio Salvatori from our team with David Bernabeu Moliner, CEO of Citibox, celebrating our partnership launch in Spain.
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Viraj Chatterjee shared thisLast week I visited São Paulo, Brazil, a city of 22 million people, extraordinary energy, and some of the most complex last-mile delivery terrain I have ever seen. Brazil is home to more than 12,000 favelas. These are high-density communities built informally, often without formal street names or addresses. For the 16 million people who live there, e-commerce access is still limited because many retailers simply do not deliver into these neighborhoods. During the visit, I toured the largest Amazon fulfillment center in Brazil and one of the most technologically advanced in Latin America. The facility processes thousands of packages per hour and plays a critical role in speeding up deliveries across the country. It even has a mascot, the Onça-Pintada (jaguar), symbolizing the speed, strength, and local identity of the operation. Thanks Ana Laura Bueno for the tour! What made the biggest impression on me, however, was seeing how these last-mile challenges are solved inside Paraisópolis, the second largest favela in São Paulo. Favela Llog is a local NGO that partners with us to deliver in these communities. Through its programs, people coming out of prison are given the opportunity to restart their lives as delivery drivers. Many grew up in the neighborhood, which helps when navigating streets and alleys that often do not appear on traditional maps. Drivers use motorcycles instead of vans or trucks to reach narrow pathways and dense areas that are difficult for larger vehicles to access. This combination of local knowledge, intentional design, and community investment helps ensure that every customer, regardless of zip code, can reliably receive their Amazon order. Thank you to the team in Brazil who made this visit possible and for showing how customer obsession can also expand opportunity in the communities we serve. Awanish Narain Singh, Charles Burch, Praveen K, Marcio Neves (He/His/Him), Rafael Caldas, Junta Funaki, Felipe Ferreira, Anand Tanna, Valeria F.
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Viraj Chatterjee shared thisLast week, I spent three days visiting partners across rural Indiana, Kentucky, and Tennessee. Ice, snow, and below-freezing temperatures covered much of the region. Roads were slick and travel required patience and caution. Despite these conditions, our partners welcomed us into their businesses and shared their stories of commitment to their communities. At Pleasantview Greenhouse and Florist in Madisonville, KY, I met the family business owners who have kept their operation running for 122 years. They've worked through more than a century of hard winters and economic change. Today, the current generation has expanded their century-old greenhouse into a diversified enterprise: Airbnbs, a florist shop, moonshine production, and now Hub Delivery, serving Amazon customers throughout their community. Their steady willingness to adapt, even when conditions are far from ideal, reflects the resilience that makes rural America extraordinary. When winter weather arrives, these partners adapt. They adjust schedules, plan routes carefully, and maintain the same level of service their communities depend on year-round. That consistency, ensuring rural communities have reliable access to deliveries regardless of the season, is why Hub Delivery matters. Thanks to our team for organizing such a meaningful visit and to all our partners for their time and hospitality! Charles Burch, Vanessa Imberti, Abbey Keane, Andrew Toomer, Rahul Pasam
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Viraj Chatterjee shared thisImagine a delivery driver entering an unfamiliar neighborhood. Everything looks fine… until a low-clearance sign appears a little too late. Miss that clearance in the system, and suddenly you’re dealing with rerouting delays, safety risks, or worse. At Amazon, accurate traffic sign detection is foundational to safe and efficient last-mile delivery. It powers route optimization, driver safety, compliance with local traffic regulations, and planning systems that need to “see” and understand the road. The challenge is that traffic signs vary wildly across regions – different shapes, colors, and designs. Many of the most critical signs, like height and weight restrictions that prevent vehicles from entering low-clearance areas, appear infrequently. This makes manual annotation expensive and time-consuming, and it’s where traditional detection models struggle most. To address this, our science team developed a two-staged pipeline that combines Grounding Distillation with No Labels (DINO) for region proposals with Contrastive Language-Image Pre-training (CLIP) for fine-grained classification, enhanced through visual-language prompt tuning. The key innovation is a k-shot learning approach that adapts foundation models using just a handful of labeled examples per sign type. We also introduced negative prompt learning to reduce false positives, which is crucial in real-world road scenarios. This approach delivers a 3x improvement in object detection accuracy and a 2x improvement in image retrieval compared to zero-shot baselines. When evaluated on the public German Traffic Sign Detection Benchmark (GTSDB) dataset, it consistently outperforms state-of-the-art few-shot detection methods across all settings. For road infrastructure cataloging, the model also reduces the searchable database size by roughly 90% when retrieving new signs. This work enables rapid deployment of traffic sign detection across new regions without massive manual labeling, making scalable, reliable navigation systems practical—not just for delivery operations, but also for autonomous driving and road inventory management. Proud of the team and excited about what this unlocks next! Want to learn more? Read all about it in our ACM SIGSPATIAL publication: https://lnkd.in/gsXCct2y Amber Roy Chowdhury, Minsoo Choi, Mohamed Moustafa, Tarun Bhatia, Ravi Garg
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Viraj Chatterjee shared thisEvery day, millions of Europeans pass through metro stations—commuting to work, heading home, running errands. Why make them go somewhere else for their packages? Over the past few years, we’ve partnered with metro operators in major cities including Barcelona, Rome, Madrid, Sevilla, and London, bringing Amazon Lockers directly into our customers’ daily routines. No extra stops. No detours. Customers simply grab their packages during their commute, exactly when and where it works for them. Metro stations offer something unique: they’re open long hours, they’re woven into daily life, and they’re where people already are. By placing lockers in these high-traffic locations, we’re removing friction and giving customers back their time. The work continues—more stations, more cities, more ways to meet customers exactly where they are!
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Viraj Chatterjee shared thisPrecision in every delivery starts with understanding the world at a very detailed level–down to the shape of every building. Every building on Earth has its own unique “fingerprint” in our system. When you order that midnight snack or last-minute birthday gift, these digital outlines quietly power our logistics by helping us group your packages with your neighbors, guide drivers right to your doorstep, and avoid mix-ups with look-alike buildings nearby. But here’s the challenge: Traditional AI models can detect buildings in satellite imagery, but the outlines they produce often look jagged or unrealistic. They might score well on metrics such as IoU (a standard quality metric that measures the overlap between the predicted outline and the actual “ground truth” building), yet still fail to capture how buildings actually look—an important detail if you’re displaying them to humans. So we rethought the problem. Instead of forcing models to commit to exact boundaries too early, we introduced “blurry coordinates”: a way of predicting probability distributions rather than fixed points. This allows models to express uncertainty where needed, produce cleaner and more consistent geometry, and recover details that older methods often tend to distort. Even better, the technique integrates smoothly with AI architectures, including transformers and multimodal LLMs, consistently improving both accuracy and outline quality. And while it’s a fun technical breakthrough, it also has a real-world impact: cleaner building outlines mean better routing, fewer delivery errors, and a more reliable mapping pipeline supporting millions of deliveries every day. This innovation earned our Geospatial Science team the Best Paper Award at ACM SIGSPATIAL GeoIndustry Workshop! Congratulations to our authors: Amber Roy Chowdhury, Mohamed Moustafa, Kuanren Qian
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Viraj Chatterjee reacted on thisViraj Chatterjee reacted on thisMegan Van Dorn graduated college, needed a job, and started delivering packages for a Delivery Service Partner (DSP) in Central New York. She didn't have a business plan. She didn't come from a business background. She just showed up and did the work. Driver. Dispatcher. Operations Manager. Then she was nominated for Road to Ownership, @Amazon's program that supports DSP employees who aspire to become DSP owners themselves. Fast forward to now, she owns Paradise Logistics Corp: 65 vehicles. Over 100 employees. Rooted in the Central New York community she's delivered in since day one. The DSP program welcomes people from all backgrounds. What unites them is community — they live in the neighborhoods they serve, they hire locally, and they're woven into the places they deliver. More stories like Megan's exist than we realize — and the DSP program is a vehicle that drives them. 🎥Watch her story: https://lnkd.in/gzm3TWzQ @transportation-shipping-logistics-at-amazonSmall business owner utilizing Amazon delivery partnershipSmall business owner utilizing Amazon delivery partnership
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Viraj Chatterjee reacted on thisViraj Chatterjee reacted on thisI'm looking for a Senior Optical Engineer to join my Last Mile Smart Delivery Technologies team! Optical sensing and display are core to our hardware-enabled innovations which protect people and accelerate operations. https://lnkd.in/grwTtp9mSr Optical Engineer, Last Mile Delivery & Technology, Last Mile Delivery & TechnologySr Optical Engineer, Last Mile Delivery & Technology, Last Mile Delivery & Technology
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Viraj Chatterjee reacted on thisExcited to share that, today, we're launching Amazon Supply Chain Services — opening up the freight, distribution, fulfillment, and parcel shipping capabilities that we've spent the last 20 years building to any business, in any industry. Companies like P&G, 3M, and American Eagle have already chosen this network to run critical parts of their supply chains and I'm proud of the teams who made this possible. We'll continue to Think Big — staying curious and experimenting often. That's how we got here. And that's how we'll keep raising the bar — for our customers and for theirs. Learn more here: https://lnkd.in/gUJq3pbR
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