Google Students

30+ offices. Thousands of Googlers. One massive global tradition. 🌏 This year’s Bike to Work Day saw group rides, morning meetups, and shared global momentum. Whether you were in it for the miles or just the post-ride treats, thanks for making this year's celebration one for the books.

Follow along for a day in the life of Ayushe: a Software Engineer on Google’s Vertex AI team! Read more about Ayushe’s work, and explore our open SWE roles ➡️ goo.gle/3QUKsAZ

Jacob, a Recruiting Manager at Google, shared his top tips for candidates interested in working at Google. Ready to apply? Visit our Careers site to explore open roles: ➡️ goo.gle/49ECKzZ

Her best advice for students? "Dream big... once you allow yourself to believe that you belong in these spaces, you’ll realize you had the ability to get there all along." See where your skills can make a global impact. Explore opportunities with our teams in Mountain View: goo.gle/4meLKSR

The biggest shift? Moving from classroom theory to the real world. "It’s one thing to learn about scalability in a classroom, but seeing how that actually translates to code maintainability at Google scale is something you just can’t simulate in college."

Samriddhi transitioned from two-time Google intern to full-time Software Engineer. "My day-to-day work focuses on simplifying our complex system, from helping advertisers optimize their campaigns to providing them with insights that move their business forward."

Meet Hitarth, a Software Developer based in Google’s Kitchener office! In his current role, Hitarth is helping shape the future of Chrome on Android, focusing on AI integration and power-user features for tablets. Initially, Hitarth was drawn to Google by its unparalleled scale. “Google’s size creates endless avenues for growth,” he explained. “For example, if I want to pivot and work on Cloud infrastructure someday, I can. I’m never stuck with one set of challenges — there’s always something new to solve.” Now more settled into #LifeatGoogle, Hitarth has been pleasantly surprised by the culture of collaboration. “Every feature we build requires creative problem-solving. My greatest assets are the people around me, and having some of the smartest minds in the world just a few steps away is incredible.” Hitarth’s advice for students hoping to follow in his footsteps? Compete in hackathons. “They teach things universities often can’t. You learn to manage a tight time crunch and lean on teamwork to hit a specific goal. Plus, they’re a great resume boost!” Ready to start your journey? Explore our open opportunities for students and early career professionals ➡️ goo.gle/4dG74eB

Leonna’s advice for those looking to make a move into tech? Give it a go. “It doesn’t matter what discipline you come from. Work hard, stay curious, reach out to people, and take a chance on yourself. If I can do it, you can too.” If you’re a student or considering a career change, your unique skills might be exactly what we’re looking for. Check out our Summer 2026 internship: goo.gle/3OHUVyO

Now on the Maps team in Sydney, she’s found that the best lessons come from the people she works with every day. “While I often ask questions, everyone is supportive and incredibly kind. You realise quickly that there are things you just can't learn from a textbook.”

From art teacher to Google Software Engineer, Leonna’s pivot started with a late-night coding puzzle. “I enrolled into University the next week, and three years and three Google Internships later, I am lucky to be here working full time.”

Attention law students: Google’s EMEA Legal Summer Institute (LSI) is accepting applications for our 2026 program across Europe, the Middle East, and Africa! LSI students will complete paid work with one of our partner law firms, as well as a week of skill-building and networking at Google. Learn more and apply by May 17 ➡️ goo.gle/4eUFuhf

To wrap up our ICLR coverage, Google Fellow and Research VP Vahab shared an inside look at his research and his top career tips for research scientists. Explore our open AI/ML roles ➡️ goo.gle/4vGQAg1

What's next for the future of robotics? Tom and Yuval — Google DeepMind Research Scientists (and long-time friends & collaborators) — shared their paths to Google and their insights on what lies ahead. Learn more about Google's work in artificial intelligence and machine learning ➡️ goo.gle/4vGQAg1

Curious about breaking into AI/ML roles without a PHD? Google Researchers Nino and Nithish sat down to answer your most common AI and ML questions from ICLR. Watch the full Q&A and explore our open AI/ML roles ➡️ goo.gle/4vGQAg1

What’s it like being a Senior Engineering Director at Google? Alex Freire shared a summary of his team's mission, insights about his time at ICLR, and a roadmap for anyone looking to make the most of AI conferences. Interested in doing similar work? Explore our open AI/ML roles ➡️ goo.gle/4vGQAg1

We caught up with Google researchers attending ICLR to get their top tips for navigating major AI conferences. Our best piece of advice? We recommend visiting Google's career site to explore open AI/ML job opportunities ➡️ goo.gle/4vGQAg1

Bruna from our Life at Google team is on the ground in Rio for ICLR! 🇧🇷 To kick off our coverage, she’s highlighting three innovative research papers Googlers are presenting at the conference. Inspired to build the future of AI? Explore our open AI/ML roles ➡️ goo.gle/4vGQAg1

Throughout the week, we’ll be in Rio spotlighting the groundbreaking research Google is presenting in this space. Whether you’re attending ICLR in Rio or following along from home, stay tuned for more coverage! Learn more: Visit g.co/jobs/AI to learn about our AI/ML roles and explore our latest openings.

The best architectural paths forward are a subject of constant debate, especially as trade-offs continue to evolve. With the advent of massive context windows, two distinct strategies for handling information have emerged: - The "All-In" Approach: Using a massive context window to keep all relevant info in the model's active memory. - The "Searcher" Approach: Using Retrieval (RAG) to pull only the necessary data from an external database. Which approach do you think is more reliable when a model needs to reason over messy, shifting, real-time data?

This week, many teams across Google are presenting their research at the 14th annual International Conference on Learning Representations (#ICLR2026)! Here’s a look at what we’re bringing to the conference, as well as the engineering puzzle keeping us busy.