What happens when experiments overlap? Two changes can look promising on their own, but tell a different story together. In our latest engineering blog, Reza Hosseini explains how the Multi-Experiment Analysis framework helps teams understand the combined impact of overlapping experiments and decide which combination to launch. He also shares the assumptions behind the framework and what we’ve learned from using it in practice. https://lnkd.in/dnE-3s9U
LinkedIn Engineering
Technology, Information and Internet
Mountain View, California 13,308 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
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https://lnkd.in/EngCareers
External link for LinkedIn Engineering
- 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
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Technology is evolving fast, but keeping pace with it is as much about people and skills as it is about the technology itself. In the latest episode of Fast Five Susan Mathew Head of HR, LinkedIn India, joins the conversation with Malai Lakshmanan to explore how AI is reshaping the skills we need, what continuous learning looks like as technology evolves, and how we can help people grow alongside it. https://lnkd.in/p/dtkgGuHE
Engineering conversations often focus on technology. This time, I wanted to talk about the people behind it. For the latest episode of Fast Five, Susan Mathew Head of HR, LinkedIn India joined me to talk about how AI is reshaping the skills we need, what it means to keep learning as technology evolves and how we can help people grow alongside it. Five questions. Some great perspectives. Watch our conversation here: #LinkedInEngineering #EngineeringLeadership #CareerGrowth #AI #Talent #TechCareers
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What happens after a member taps something on LinkedIn and how do we trace that journey all the way to the backend? In our latest Engineering blog, LinkedIn engineer Aashay Mittal explores how we used OpenTelemetry to trace the member journey from MemberTap to backend, helping connect the dots across the end-to-end experience https://lnkd.in/dHxf7JBj
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Processing high volumes of events at scale requires infrastructure that can evolve with growing demands. In our latest Engineering blog, LinkedIn engineers PRAVESH GUPTA and Pranav Mutharia go behind the scenes of how LinkedIn rebuilt its tracking infrastructure, sharing the journey to scale, migrate and harden a high-volume event pipeline. https://lnkd.in/da89UAB8
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As Spark and Flink workloads continue to grow, moving data efficiently at scale becomes increasingly important. In our latest Engineering blog, LinkedIn engineer Aravind Patnam takes us inside how we’re using Apache Celeborn to scale shuffle infrastructure for Spark and Flink, enabling more efficient and reliable data processing. https://lnkd.in/dA5eZcin
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Writing the query is often the easy part. Knowing which data to trust and how to use it correctly is harder, for both people and AI agents alike. LinkedIn engineers Ilho Ye, Wei Li and Jianlong Zhong take us inside the data context layer we built to bring together AI-generated context and human expertise, helping people and agents find the right data and use it correctly. https://lnkd.in/gtJj2AqJ
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AI slop is evolving fast. The technology to tackle it needs to evolve even faster. How do you build systems that can adapt at the scale of LinkedIn, while continuing to surface authentic, valuable content? Tim Jurka takes us behind the engineering of how LinkedIn is approaching this challenge and what we’re learning along the way https://lnkd.in/dtt74jWg
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As AI products become more capable, the challenge isn't just building them, it's scaling them efficiently. In a recent interview with Modern CTO, CTO of Engineering Erran Berger explores one of the defining engineering challenges of the AI era: growing product capability while maintaining efficiency. From infrastructure and systems design to workforce transformation, he shares what it takes to build AI at scale. https://lnkd.in/p/dFMcEpuS
As AI products become more capable, they also become more compute-intensive and so the engineering challenge is figuring out how to keep improving those products, without allowing costs to scale at the same rate. This is not because we're trying to do less, but because we're trying to do more across our platform to create better experiences for our members and customers. That means constantly asking ourselves: how do we grow capability, without significantly scaling compute? I recently joined Joel Beasley on Modern CTO to talk about that challenge and why efficiency is really a full-stack problem, spanning everything from GPU utilization and cost attribution to the systems that turn AI advances into better products. We also discussed how AI is changing the way engineering organizations operate and why helping employees build AI skills is an investment in their future. Check out the podcast and give it a listen! YouTube: https://lnkd.in/dFE6fRtW Spotify: https://lnkd.in/dWf2EZQg Apple Podcasts: https://lnkd.in/dxX7eabN
Scaling AI Efficiency at LinkedIn with Erran Berger, CTO of Engineering
https://www.youtube.com/
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What does it take to build AI systems people can trust? Director of Data Science, Hitesh Manwani joins Head of India Engineering Malai Lakshmanan for the latest Fast Five conversation on responsible AI, the role of data science in building trustworthy experiences, and why trust remains the foundation of innovation as AI continues to evolve. https://lnkd.in/d_yzKBSF
AI is changing the way we build, but trust remains the foundation. In the latest episode of Fast Five with Malai, I sat down with Hitesh Manwani, Director of Data Science, Trust at LinkedIn, to explore the role of data science in shaping products that deliver real value, why trust must remain at the heart of AI innovation, and the responsibility that comes with building intelligent systems at scale. Watch the full conversation here to hear Hitesh's perspective on data science, trust, responsible AI, and building products that create meaningful impact at scale. #LinkedInEngineering #AI #DataScience #TrustAndSafety #EngineeringLeadership #ResponsibleAI
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How do you optimize your LinkedIn profile in today's AI-powered world? Mahima Hans sits down with Nithya Rajagopalan to explore practical tips for building a stronger professional brand, unlocking opportunities and making the most of LinkedIn's AI-powered experiences. https://lnkd.in/dPRCH3h9
How do you optimise your LinkedIn profile to get shortlisted? I asked this to Nithya Rajagopalan, Senior Director of Engineering at LinkedIn. Her answer was simple: keep your profile updated, but don’t stop at listing your skills, back them with evidence. Your LinkedIn profile should clearly reflect your skills, experience, education, certifications, and projects. But more importantly, show the evidence behind those skills. - What did you build? - What did you work on? - What impact did you create? That trail of evidence helps AI systems understand your experience and gives recruiters the context they need to evaluate your profile. We also had a detailed discussion about LinkedIn Hiring Assistant and what goes into building AI-powered hiring experiences at scale. There was also an interesting discussion on how the role of engineers is evolving as AI becomes part of the systems we build. I’ve shared the full conversation in the video. Watch it to hear Nitya break down the engineering and AI thinking behind LinkedIn’s hiring experiences.