LinkedIn Engineering’s cover photo
LinkedIn Engineering

LinkedIn Engineering

Technology, Information and Internet

Mountain View, California 12,567 followers

Transforming the way the world works.

About us

Powered by the world’s most trusted and largest professional platform, our vision is to create economic opportunity for every member of the global workforce. Our engineers at LinkedIn collaborate cross-functionally to ethically craft quality consumer, business-to-business (B2B) marketing, B2B sales, and talent/learning products — to help job seekers, businesses, and learners maximize their potential. For more information, visit: https://lnkd.in/EngCareers.

Website
https://lnkd.in/EngCareers
Industry
Technology, Information and Internet
Company size
10,001+ employees
Headquarters
Mountain View, California
Founded
2003
Specialties
AI & Machine Learning, Backend (Apps) Engineering, Data Science, Engineering Leadership, Frontend (UI) Engineering, Mobile Engineering, Site Reliability Engineering (SRE), Systems & Infrastructure (SI), Technical Program Management (TPM), and Trust & Safety (QA)

Updates

  • Engineering isn’t just about building systems — it’s about building systems that work for everyone. That only happens when teams bring a wide range of perspectives into the room. For International Women in Engineering Day, CTO of Engineering Erran Berger and Shalini Agarwal shared powerful insights on why diverse engineering teams drive better architecture, better decision‑making, and ultimately better products.

    At LinkedIn, we're driven by our mission to create economic opportunity for every member of the global workforce. We take that commitment to 'every member' seriously. It's why we make sure that diverse thinking and perspectives go into the building of our products. For International Women in Engineering Day, I sat down with Shalini Agarwal, Sr Director of Engineering for Talent Marketplace and one of the leads for LinkedIn’s Women in Technology community. We dug into why diverse engineering teams aren’t just good for equity—they’re essential for any business seeking to build better, more human‑centered products. And we explored what inclusive management looks like in practice and how leaders can create environments where every engineer can thrive. #INWED

  • In the latest episode of Fast Five, Head of Engineering in India Malai Lakshmanan speaks with Deepthi Singh Sharma about how much intention it takes to innovate safely at scale. Deepti brings clarity to what modern engineering demands as AI reshapes the craft.

    Many people assume AI knows the answer. As Deepthi Singh Sharma points out in the latest episode of Fast 5, it doesn't. At its core, AI is a probabilistic system making highly informed guesses and for engineers building with AI, that distinction matters. Deepthi and I spoke about how generative AI is changing the craft of engineering, what it takes to keep LinkedIn trusted and safe at scale, and why curiosity remains one of the most important things leaders can nurture in their teams. What I admire most about Deepthi is her ability to combine deep technical expertise with thoughtful leadership. She's also a great example of the impact women engineers are having, not just in shaping technology, but in shaping the future of our industry. Always enjoy conversations that challenge how we think about both technology and leadership. #LinkedInEngineering #AIAtWork #WomenInEngineering #IndiaTech

  • AI isn’t only about inventing brand‑new capabilities — it can elevate the moments our customers already rely on. LinkedIn's Swetha Karthik and Prakruthi Prabhakar chat with CTO of Engineering Erran Berger about how thoughtful engineering shapes a more refined, member‑first experience.

    Every detail of the LinkedIn experience is thoughtfully engineered, and notifications are one place where that craftsmanship really shows. They need to be helpful, timely, and respectful of your attention - never just more noise or overwhelming for our members. I sat down with Swetha Karthik and Prakruthi Prabhakar, who lead the tech behind notifications systems, to explore how our teams use AI to fine‑tune notifications so they strike that balance and feel meaningful. From model design to delivery logic, there’s a lot happening behind the scenes to get this right. Check it out!

  • Waste streams are full of untapped value, but tech from AMP shows how an AI‑driven approach to isolating organics and producing biochar could reshape the economics of recycling and landfill diversion. President of Platforms & Digital Work for Microsoft and LinkedIn Mohak Shroff learned how AMP is engineering tech that could create measurable climate impact.

    Most recycling tech stops at sorting. AMP is designing what comes after that. Their AI can already detect tiny organic fragments on a belt, identifying food scraps, yard debris, and other carbon‑rich materials with surprising precision. As Mikaela Juzswik explains in this episode of Built Different, AMP is using that capability to extract those materials and process it to produce biochar - a stable, long‑lived carbon form with real industrial utility. It’s a practical answer to the question of what to do with everything that can’t be recycled or doesn’t have resale value - the stuff that usually gets buried in a landfill. Solving that is one way AMP is building for a more eco-friendly future.

  • In the AI era, mentorship isn’t top‑down — it’s a loop. This conversation between LinkedIn Distinguished Engineer Karthik R. and Sr Software Engineer Noelle Lim is a great reminder that senior engineers bring pattern recognition, while early‑career engineers bring fresh instincts shaped by today’s tools. When both sides teach and learn, teams move faster and think smarter.

    Mentorship shouldn’t be a one-way street but more of a two-way partnership. Sitting down with Karthik R. with Karthik R., we explored how senior and early-career engineers can navigate this AI moment together.  My piece of advice: the best leaders are active listeners that work to scale the impact of their entire team. So if you’re a leader, create the space for early-career engineers to shape the way teams work, and not just execute. There is always something to learn from one another, whether you are just starting out or deep into your career. If you’ve benefited from two-way mentorship, I’d love to hear the lessons that stuck with you!

  • As Prashanthi Padmanabhan shared, Hiring Assistant is now live in French and German! Under the hood, our engineering teams built a reusable linguistic rubric framework that ensures native-quality output across languages that’s culturally accurate.  Read the blog here: https://lnkd.in/eBTXzv6S

    LinkedIn's Hiring Assistant just took a big step forward to help more recruiters work smarter. Today we launched Hiring Assistant in French and German. Bringing agentic products to international markets at scale requires us to treat language quality as a first-class engineering problem. Generic localization approach or just using multilingual LLMs will not cut it. It's a deep engineering challenge, as we must ensure native language quality for dynamically generated outputs and global scale. We've solved this by building a reusable system: an automated linguistic rubric framework that abstracts language nuances out of individual prompts and agents. This system delivers high-quality, culturally appropriate recruiter experiences with repeatable efficiency, providing the foundational velocity needed for our Talent Solutions business to scale across 10+ languages -including Spanish, Portuguese, Dutch and Italian, which are coming soon. Here is the behind the scenes of how we built this platform for international markets:  https://lnkd.in/gf28DQ7J Massive kudos to Nikhil N Jannu Franklin Geo Francis Arunima Chaudhary Anirban Ghosh Karthi Vijayakumaar Manav Sharma Daniel Hewlett Jonathan Pohl Greg Pounds Xie Lu Xiaoyang Gu Anu Krishnan and many others for making Hiring Assistant multilingual! #LinkedInHiringAssistant

  • We hear it all the time: people are curious about building with AI, but taking the first step feels intimidating. That’s exactly why LinkedIn's Hack Week matters. It creates room for anyone—no matter their background—to pause, experiment, and see what these tools can actually unlock.   Employees like Justin Marsh remind us what happens when you show up with curiosity instead of pressure. He didn’t set out to craft a flawless prototype. He set out to stretch himself, try things, and learn along the way.   That shift in mindset is often the real breakthrough. When you stop chasing perfect, you give yourself permission to build.

  • The process of learning should always be a priority. As an engineer, that can be difficult when productivity is at a premium and everything feels like it should be done with speed.   In an episode of Dev Interrupted, Karthik R. and Andrew Zigler discuss their experiences with professional and technical learning, including prioritizing durable learning, two-way mentorship, and building agents and memory that scale.   See the episode clip below, and check out the full episode: https://lnkd.in/gJqJn9xK

  • ML and AI are undergoing constant innovation across all layers of the technology stack. One of the biggest catalysts is the evolution of infrastructure.    Animesh Singh, Senior Director of ML and AI platforms, sat down with Aishwarya Srinivasan for an episode of Ctrl+Alt+AI. If you're curious about the way AI infrastructure is evolving and how LinkedIn is scaling its infrastructure for the agentic era, this is the episode for you.   Check out their full conversation: https://lnkd.in/gJ6TAX_B

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  • We chased a silent 10–15 second freeze across our Feed systems and traced it back to something simple: a HashMap resize that triggered a system-wide lock.   The fix? One line of code.   When we're building reliable systems it isn’t only about architecture. It’s about understanding how systems behave under real-world conditions, down to the details. And it's the kind of deep, cross-stack problem-solving our engineering teams in India are driving every day.   In our latest engineering blog, the team breaks down how they uncovered the 58 million key threshold and the single line that resolved it.   Read the full deep dive: https://lnkd.in/enwE5yTZ

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