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Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Data Platform team at Figma builds and operates the foundational systems that power analytics, AI/ML, and data-driven decision-making across the company. We serve a diverse set of stakeholders, including AI researchers, machine learning engineers, data scientists, product engineers, and business teams that rely on data for insights and strategy. Our team owns and scales critical platforms such as the Snowflake data warehouse, ML Datalake, orchestration and pipeline infrastructure, and large-scale data ingestion and processing systems, managing all data flowing into and out of these platforms. Despite being a small team, we take on high-scale, high-impact challenges. In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion and reverse ETL capabilities for new product use cases, and strengthening data quality, reliability, and compliance at every layer. If you're passionate about building scalable, high-performance data platforms that empower teams across Figma, we'd love to hear from you! This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence across Figma. Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company. Manage and evo

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! At Figma, infrastructure is at the heart of everything we build. As a Software Engineer on our Infrastructure team, you’ll help design, build, and operate the systems that power our real-time collaborative design tools used by millions of people worldwide. We’re scaling fast, and we’re looking for experienced distributed systems engineers across a variety of teams. Whether you’re passionate about storage, compute orchestration, developer tooling, networking, or real-time data systems, this role offers an opportunity to shape the technical foundation of one of the most beloved design platforms in the world. This is a full time role that can be held from one of our US hubs or remotely in the United States. What You’ll Do at Figma: Design, build, and maintain scalable and reliable infrastructure systems that support product innovation and user collaboration at scale. Architect and evolve distributed systems including storage platforms, streaming infrastructure, and compute orchestration. Improve developer experience by building internal platforms, CI/CD systems, build tools, and APIs. Collaborate across product and infrastructure teams to design secure, maintainable, and performant systems. Participate in shaping platform strategy, roadmaps, and engineering best practices across the organization. Debug and resolve complex production issues that span services and layers of the stack. Mentor engineers and foster a culture of collaboration, inclusivity, and technical excellence. We’d Love to Hear From

ROLE/RESPONSIBILTIES: We are seeking a quant research intern to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing. The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may include: Using NLP to construct features from varied datasets Formulating research hypotheses to derive alpha Building and testing the performance of trading signals based on NLP and financial features Launching identified signals into production REQUIREMENTS: Bachelor’s, Master’s or PhD candidate in computer science or other quantitative discipline Proficient in Python and general software engineering principles (github, testing, dev workflow) Strong understanding of machine learning and statistics Prior research experience preferred Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred Data science stack familiarity preferred An interest in financial markets Great attitude A collaborative mindset Commitment to the highest ethical standards ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

ROLE/RESPONSIBILTIES: We are seeking a NLP engineer for a NLP research team within Point72. The ideal candidate has a track record of developing modern NLP solutions, including the use of LLMs, agents, RAG, open-source models fine-tuning and deployment, etc. Responsibilities include: Exploring and combining rich internal and external textual datasets Building GenAI solutions, leveraging both internal models and external APIs Formulating research hypothesis to derive alpha Post-training models for specific tasks Benchmarking LLM approaches internal tasks We believe the investment world offers unique opportunities to use modern NLP methods. We are a team ideally situated for that, having access to both internal and commercial datasets, with an end-to-end research philosophy and direct portfolio impact. REQUIREMENTS: Bachelor, Master’s or PhD graduate or candidate in computer science or another quantitative discipline Experience in NLP, particularly LLMs. Proficient in Python, SQL and general software engineering principles (github, testing, etc.) Data science stack familiarity Interest in financial markets Collaborative mindset ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment. Responsibilities: Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor Manage day-to-day execution of the team's work Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment Coach and support your reports in understanding, and pursuing, their professional growth Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you: Have 1+ years of management experience in a technical environment, particularly performance or distributed systems Have a background in machine learning, AI, or a similar related technical field Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development Excel at building strong relationships with stakeholders at all levels Are a quick learner, capable of understanding and contributing to discussions on complex technical topics Have experience manag

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About the Role The Device Experience team at HP IQ builds intelligent Windows applications that help people work more naturally with their PCs. We are looking for a senior engineer who enjoys creating thoughtful, visually compelling software. You will work closely with design and product to turn ambitious ideas into responsive interfaces, clear interaction flows, and dependable application behavior. Our work spans custom UI, animation, reusable controls, asynchronous workflows, and integration with local AI and system services. You will help deliver new experiences while improving the architecture of an existing application. AI coding assistants are an important part of how we work. We value engineers who use them effectively to investigate, prototype, implement, and test, and who take responsibility for the resulting code and user experience. Our primary stack is C#, .NET, and WPF, with WebView-based content and Windows platform integrations. What You Will Do Help shape features from the initial user problem through implementation and release. Turn designs and incomplete requirements

Asana’s rapid growth brings new challenges in keeping our systems fast, reliable, and resilient. As our product evolves, we’re making a major investment in reliability – and building a brand new SRE team in Warsaw is a key part of that strategy. This is your chance to help shape it from day one. This isn’t a traditional “ops” role – we’re looking for strong software engineers who are passionate about building reliable, distributed systems. You’ll work closely with a small SRE team in San Francisco, infrastructure engineers in Reykjavik, and an established infrastructure team in Warsaw. Warsaw will be a significant hub for our future infrastructure engineering and operations. As one of the first engineers here, you’ll have a real say in how we build reliable infrastructure, manage incidents, and support the rest of the company. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Influence the future of Asana’s SRE practice, especially as we grow the Warsaw team. Lead reliability-focused projects across our stack – from infrastructure to tooling to incident response. Define and implement Asana’s incident management process – we’re investing here, and you’ll help shape how it works. Build internal platforms and frameworks that help other teams improve the reliability of their services. Be part of (and help shape) a sustainable on-call rotation – shared across teams in Warsaw, San Francisco, and Reykjavik. On average, we handle ~1 page per day, but it’s not constant, and we care about keeping things sane. Work with our stack: AWS, Kubernetes (EKS), Datadog, MySQL (RDS), ElasticSearch (OpenSearch), Redis

Lead AI Engineer (Senior/Principal Consultant) Location: London (Hybrid) | Practice Area : Technology & Engineering | Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We’re looking for a Lead AI Engineer (Senior/Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader, you’ll architect AI solutions, embed them within enterprise environments, and drive impactful outcomes through advanced engineering, scalable pipelines, and deep cross-functional collaboration. What You’ll Do Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video) Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption What We’re Looking For Bachelor’s degree or higher in Computer Science, AI, or related STEM fields Hands-on experience deploying LLMs and multi-modal models at scale Strong engineering background in Python with proven backend and API development skills Solid understanding of scalable MLOps, observability, and cloud-native AI deployment Excellent communication, problem-solving, and project management skills in agile environments Bonus Points For Experience with agentic frameworks (e.g., LangChain, LlamaIndex) Experience in deep learning frameworks and front-end development Familiarity with Langfuse, Langsmith, or other LLM observability tools Understanding of Model Context Protocol

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 Staff Engineer on the User Activation team, you will play a critical role in driving the technical vision, architecture, and execution for horizontal product experiences that accelerate customer adoption and growth. Sitting at the entry point for all Databricks customers, you will help guide a team of ~20 software engineers to create seamless onboarding flows, intuitive workspace experiences, and partner integrations that power Databricks expansion. The impact you'll have: Define and drive the strategy for customer onboarding, workspace experience, account management, and other horizontal product experiences. Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive product-led growth. Lead architectural decisions to ensure performance, reliability, and simplicity across core user flows. Hands-on full-stack software development to create dynamic, user-centric experiences. Drive best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations. Collaborate cross-functionally with teams developing vertical product experiences (Lakehouse Platform, SQL Warehouse, AI/BI Dashboards) and infrastructure teams to ensure seamless integration and innovation. What we loo

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

Role/Responsibilities: We are seeking a quantitative researcher to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing. The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may include: Using NLP to construct features from varied datasets Formulating research hypotheses to derive alpha Building and testing the performance of trading signals based on NLP and financial features Launching identified signals into production Requirements: Bachelor’s, Master’s or PhD degree in computer science or other quantitative discipline Proficient in Python and general software engineering principles (github, testing, dev workflow) Strong understanding of machine learning and statistics Prior research experience preferred Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred Data science stack familiarity preferred An interest in financial markets Great attitude A collaborative mindset Commitment to the highest ethical standards About Point72: Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here.

RDQ426R193 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. Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration. As a Senior Engineering Manager for Search, you’ll play a critical role in building and scaling our next-generation Search product — spanning Vector Search, Keyword Search, and Search Quality. You’ll drive the design and evolution of a highly-performant, cost-efficient, and developer-friendly Search stack that enables customers to build AI applications with accuracy, speed, and scale. Beyond hands-on contributions, you’ll help define the long-term vision, mentor senior engineers, collaborate across teams, and lead strategic efforts that expand the technical and business impact of Search at Databricks. Check out our recent blog post: Decoupled by Design: Billion-Scale AI Search The impact you will have: Lead a team of talented software engineers to design, build, and operate the next-generation cloud-native Search services. Drive innovation across Vector Search, Keyword Search, and Hybrid Search capabilities to improve relevance, latency, and cost efficiency. Build a strong partnership with product and research teams to define the roadmap for Search Quality, including ranking models and evaluation frameworks. Mana

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. We are looking for a technically-capable product leader to head up AI Design at Fin. Fin is the #1 AI agent for customer service — a full-stack, vertically integrated AI system powered by our own in-house models, Apex, designed specifically for customer experiences. The role is to lead the Design function within our AI Group, where our custom models and core Fin functionality are developed. You will be managing our AI Designers (currently 3 Staff/Principal level AI Designers). You will work directly with AI Engineers and Scientists in our AI Group , and Product Designers and teams in our R&D group. We believe that leading AI Design is a new type of product leadership role that combines technical, product, and leadership qualities. This includes shaping how the Fin AI models and harness behave — how they reason, respond, and improve over time. The experience is defined as much by model behavior, evals, and iteration loops as it is by UI. We’re looking for someone to lead in that world.

Analytics Engineer Prolific Prolific is not just another player in the AI space—we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The role As an Analytics Engineer in the Data Infrastructure Team at Prolific, you’ll be at the forefront of transforming and maintaining Prolific’s data infrastructure as the way people work with data changes rapidly. Your work will be instrumental in redesigning and scaling our data stack, ensuring data pipelines are robust, efficient, and reliable, and that our data is ready to be queried by people and AI systems alike. By owning and optimising our analytics codebase and semantic layer, you’ll empower teams across the business to get trustworthy answers, whether through BI dashboards or natural language questions. You’ll help shape how we bring LLMs and agents into analytics engineering safely and effectively, and you’ll bridge the gap between technical and non-technical stakeholders so that complex data solutions are clearly understood and aligned with business goals. What you’ll bring to the role Expertise in dbt & SQL: Deep experience with dbt and SQL to design, build, and maintain scalable data models. Semantic Modelling: Experience defining metrics, entities, and business logic in a semantic layer (e.g. dbt Semantic Layer/MetricFlow, Cube, LookML or similar), with an understanding of what makes a model reliable for natural language querying. Applied AI in Data Workflows: Hands-on experience using LLMs in data work, such as classification, extraction, or enrichment within transformations, and an understanding of how to evaluate, test

Note: if you are an intern, new grad, or staff applicant, please do not apply using this link and visit our jobs page for those specific postings. Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the Organization Secure Frameworks: We provide security guarantees for common threats, helping teams secure their services by default. We build and maintain core application-layer security libraries and frameworks for development teams, including web security frameworks, cryptography libraries, and other threat mitigations across the Stripe technology stack. More recently, our scope has expanded to protective measures for AI agents. We are a hands-on engineering team that builds security protections and frameworks, rather than conducting security reviews. Core Infrastructure : We’re the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency and scalability of these systems. Developer Infrastructure : We’re responsible for the productivity of all developers at Stripe. Ensure Stripe’s engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Reliability Insights and Excellence : We build tools and frameworks