Member of Data Staff (Data Acceleration)

About the Role The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. Key Responsibilities Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. Debug com

P-925 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a Senior Frontend Engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products. Below are some example experiences you'll create for our customers to achieve the full project lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. Simple workflows to create, configure, and manage large-scale compute clusters, networks and data sources. Create, deploy, test, and upgrade complex data pipelines with powerful features to visualize data graphs. Seamless onboarding and management for all members of an organization to become data-driven. Provide a great SQL-centric data exploration and dashboarding experience on Databricks An interactive environment for collaborative data projects at massive scale with an easy path to production. What we look for: 5+ years of experience with HTML, CSS, and JavaScript Experience leading large multi-quarter efforts with a demonstrated customer or business impact Passion for user experience and design and an understanding of front-end architecture Comfortable work

Perplexity is AI for people who expect more. This role brings that standard to how we understand our users, shape our product, and decide what to build next. We're looking for a data scientist who can turn product questions into clear decisions. You'll work across product, engineering, growth, design, and user research to understand user behavior, define metrics, design experiments, and identify the highest-leverage opportunities for the company. The data team is AI-native by default. We use AI to accelerate analysis, write and review code, explore hypotheses, document data, generate first drafts, and automate recurring workflows. But the core of the role is still judgment: asking the right question, choosing the right metric, designing the right test, and knowing when the answer is strong enough to act on. What You'll Do Develop product insights - analyze user behavior to inform product roadmap, accelerate adoption, and identify opportunities to improve the user experience. Design and analyze experiments - form hypotheses, define success metrics, run A/B tests, interpret results, and turn findings into product recommendations. Define the metrics that matter - build the metrics, guardrails, dashboards, and reporting workflows that help teams understand product and company health. Partner across functions - work closely with engineering, product, growth, design, and user research to answer ambiguous questions and drive decisions. Build reusable data assets - create tables, models, and documentation that make analysis faster, more consistent, and easier for humans and AI systems to use. Use AI to scale data science - automate recurring analysis, build AI-assisted workflows, improve documentation, and turn one-off investigations into repeatable systems. Tell the story clearly - communicate findings, assumptions, uncertainty, and recommendations in a way that helps teams make decisions. What We're Looking For 6+ years of experience as a data scientist or closely related

Perplexity is AI for people who expect more. On the data team, that means building the systems that make our data reliable, understandable, and usable by both humans and AI. We're looking for an analytics engineer or data engineer who wants to build the foundation for an AI-native data organization. You'll design core data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that power the entire company: helping teams make strategic decisions, operate the business, and move faster with trusted data. You'll also make sure those systems are secure, privacy-aware, and legible to AI agents, data scientists, and the rest of the company. This role is for someone who can operate at the boundary of analytics engineering, data engineering, data governance, and internal product. You care about dimensional modeling, dbt standards, cost-aware warehouse design, access controls, privacy, and the details that make data trustworthy. You also believe AI should make the data stack faster, easier to maintain, and more accessible across the company without weakening security or governance. What You'll Do Build the core data foundation - design and maintain high-quality data models, marts, and pipelines that make analysis fast, reliable, and reusable. Manage the data warehouse - help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene so the platform scales cleanly. Make the warehouse AI-readable - own the documentation, semantic context, metadata, lineage, and retrieval patterns that AI systems depend on to understand and query Perplexity's data correctly. Own data modeling standards - define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes. Lead data governance practices - define standards for access, ownership, lineage, documentation, retention, quality, and sensitive data handling across the analytical warehouse.

RDQ426R282 Databricks is building the world's best and most secure platform for data and AI. We innovate and deploy industry-leading solutions in security, compliance, and governance. As a member of the Trust and Safety Data Science team, you will work on projects critical to ensuring the security and compliance of the Databricks Platform. Our customers depend on Databricks to keep their data safe, all while orchestrating millions of virtual machines across three clouds in dozens of regions around the globe. Our engineering teams build highly technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is critical to making customers successful on our platform. We serve many companies with varying security and compliance needs. To efficiently serve these markets, we need to understand how customers use our existing features. This requires data-driven analysis of all aspects of security programs at Databricks. Customers also trust Databricks with their most valuable data and we have the mission to build the most trusted data analytics and ML platform in the world. We’re looking to expand our Trust and Safety Data Science team. You will join a group of “full stack” data scientists who partner with engineering and security teams, focusing on strategic plans that make Databricks secure and safe for our customers. The team will use statistical and machine learning techniques for fraud and abuse detection on our platforms using state of the art methods . You can read more about some of our efforts in this blog post . The work in fraud and abuse detection is dynamic and essential, offering an opportunity to make a substantial impact in maintaining the security and efficiency of business operations. More information is available at https://www.databricks.com/trust . The impact you will have: You will develop and implement Machine Learning mod

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is looking for a Staff Data Engineer! This person will be a key member of the growing data team, supporting one of the fastest growing B2B SaaS startups to achieve unicorn status. At Drata, we’re on a mission to help build trust across the internet! Data accuracy is an essential cornerstone of our mission. We are looking for a senior data engineer that can help us strategize