Companies

All companies

• Airbnb

  Airbnb operates a two-sided marketplace connecting guests with hosts for stays and experiences. Its engineering covers search and ranking, pricing, booking and payments, trust and safety, messaging and reviews, and web and mobile clients, supported by shared service infrastructure and data and machine-learning platforms.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Infrastructure / platform engineering, and more

  Not verified1 source

• Amazon

  Amazon’s engineering spans retail and marketplace systems, fulfillment and logistics software, devices, advertising and the AWS cloud. Much of the work is service-oriented backend development under high load, with engineers responsible for operating what they build; the official prep pages stress scaling concepts, data stores including non-relational databases, and distributed architectures.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering

  Official guidance4 sources

• Anthropic

  Anthropic develops the Claude family of AI models and the products built on them, including the Claude apps, Claude Code and an API platform. Its careers page says engineers do substantial research and researchers do substantial engineering. Work spans model training and evaluation, safety and interpretability research, training and inference infrastructure, and product and platform engineering.

  Relevant roles: General software engineering, Infrastructure / platform engineering, ML engineering, Research-oriented ML implementation, and more

  Official guidance2 sources

• Apple

  Apple’s Software and Services organization builds the operating systems, frameworks and apps for Apple devices and runs online services such as iCloud, Apple Music, Maps and Siri. The careers page splits the work into teams ranging from Apps and Frameworks, Operating Systems, GPU and Graphics and Wireless Software to Cloud and Back-End Infrastructure, DevOps and Site Reliability, Security and Privacy, and Machine Learning and AI, so the relevant engineering domains depend strongly on the team.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Low-level software systems, and more

  Partial: no verified loop1 source

• Bloomberg

  Bloomberg’s engineers build the Bloomberg Terminal and related products for financial professionals: real-time market and enterprise data, analytics, trading tools, news, secure biometric access and integrated communications. Its tech page highlights AI, machine learning and natural language processing over financial data and says most of its software is written in C++, JavaScript/TypeScript and Python. Relevant areas include high-throughput, low-latency data systems, large distributed services, language-level depth in C++ or Python, and applied ML.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Partial: no verified loop3 sources

• Citadel / Citadel Securities

  Citadel (an investment firm) and Citadel Securities (a market maker) recruit campus engineers through one shared process. According to Citadel’s engineering FAQ, engineers build data ingestion pipelines for trading desks, scenario-analysis frameworks, analytics tools over datasets of millions of rows per day, cloud microservice architectures and a browser-based real-time trading dashboard, designed to keep working through market volatility. Relevant areas include data-intensive backend systems, performance and reliability, and close collaboration with traders and researchers.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Official guidance2 sources

• Cloudflare

  Cloudflare operates a large global network in front of customers’ websites, applications and corporate networks, providing CDN caching, DNS, DDoS mitigation, web application firewalling and Zero Trust access, plus a developer platform for running code and storing data at the edge. Engineering work centers on networking protocols (DNS, TCP, TLS, HTTP/2, HTTP/3 and QUIC, BGP), high-performance proxies and systems programming, configuration and control planes that must reach many data centers quickly and safely, observability and incident response, and security.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Partial: no verified loop2 sources

• Databricks

  Databricks builds a data and AI platform (the lakehouse) on technologies such as Apache Spark, the Photon engine and MLflow. Engineering spans distributed query and data-processing engines, storage layers, stream processing, cloud infrastructure, developer-facing front ends and ML and GenAI tooling, which is why its engineering guide includes systems-programming and database-specific interviews.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Distributed systems engineering, and more

  Official guidance2 sources

• Google

  Google’s engineering covers Search, Ads, Google Cloud, Android, YouTube, Workspace and AI products, largely built on shared large-scale infrastructure. Software engineering roles span backend and distributed systems, mobile and web clients, infrastructure and SRE, and ML systems.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Distributed systems engineering, and more

  Official guidance3 sources

• Google DeepMind

  Google DeepMind is Google’s AI research and model-building organization, behind Gemini, Veo, AlphaFold and other systems. Its careers page describes Research Engineers (implementing, optimizing and scaling models and building distributed-computing infrastructure), Software Engineers (reliable, efficient software at scale), Research Scientists, and product, program and responsibility roles.

  Relevant roles: General software engineering, ML engineering, Research-oriented ML implementation, Training / inference infrastructure, and more

  Official guidance2 sources

• Hudson River Trading (HRT)

  Hudson River Trading is an algorithmic trading firm. Its October 2025 engineering post splits engineering into Trading Tech, focused on latency (exchange market data, order entry, FPGA/ASIC acceleration, trade processing), and Research & Development, focused on scale (storage, data centers, CPU/GPU clusters, job scheduling, data pipelines and research tools), each with platform teams and engineers embedded with trading teams. Work ranges from Verilog and low-level C++ to Python services and TypeScript/Python full-stack tools.

  Relevant roles: General software engineering, Low-level software systems, Backend engineering, Distributed systems engineering, and more

  Official guidance1 source

• Jane Street

  Jane Street is a quantitative trading firm whose software engineers build trading systems, market-data and order-handling infrastructure, research and risk tools, and the libraries, compilers and developer tooling behind them. The firm is known for its extensive use of OCaml, yet its own guidance tells candidates to interview in their strongest language. Relevant areas include careful, correct code, data-structure design, performance and systems programming.

  Relevant roles: General software engineering, Backend engineering, Low-level software systems, Distributed systems engineering, and more

  Official guidance3 sources

• Meta

  Meta builds consumer-scale social, messaging and media products (Facebook, Instagram, WhatsApp, Messenger, Threads), the ads systems that fund them, AI models and assistants, and AR/VR devices. Engineering work spans mobile and web clients, product backends, large-scale distributed storage and data infrastructure, and ML systems for ranking and recommendation. The Meta-authored guide summarized here covers the general software engineer loop.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Distributed systems engineering, and more

  Official guide via mirror2 sources

• Microsoft

  Microsoft’s engineering spans operating systems and developer tools, productivity and collaboration software, the Azure cloud platform, gaming, security, and AI products and infrastructure. Depending on the team, software roles lean toward distributed cloud services, systems software, networking, data science or ML.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Official guidance2 sources

• Mistral AI

  Mistral AI builds open and commercial AI models and products: an agent and app platform (Studio), model training and customization (Forge), coding agents (Vibe) and an AI cloud for training and inference. Its careers page groups teams into Science, Product and Engineering, Go-to-market and Solutions, and Corporate.

  Relevant roles: General software engineering, Backend engineering, Applied AI engineering, ML engineering, and more

  Official guidance1 source

• Netflix

  Netflix runs a global streaming service on cloud infrastructure and its own content-delivery network, Open Connect, alongside commerce and billing systems, studio and content-production software, games, advertising technology, and personalization and ML platforms. Its engineering careers page lists teams across ads, commerce, content and business products, games, infrastructure, and member systems and ML, with engineering hubs mainly in the U.S. and Poland.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Partial: no verified loop3 sources

• NVIDIA

  NVIDIA designs GPUs and accelerated-computing platforms along with the software that makes them usable: drivers, compilers, CUDA libraries, AI training and inference software, networking, and systems for data centers, autonomous vehicles, robotics and graphics. Software roles range from low-level systems and performance engineering to ML frameworks and AI infrastructure.

  Relevant roles: General software engineering, Low-level software systems, Infrastructure / platform engineering, ML engineering, and more

  Official guidance1 source

• OpenAI

  OpenAI develops frontier AI models and ships them through ChatGPT, Codex and an API platform. Engineering work spans research engineering and model training, large-scale training and inference infrastructure, applied AI and product engineering, safety work, and conventional backend, frontend and platform engineering.

  Relevant roles: General software engineering, Backend engineering, Applied AI engineering, ML engineering, and more

  Official guidance1 source

• Palantir

  Palantir builds software platforms (Foundry, Gotham, AIP and Apollo) that integrate an organization’s data, model it as a shared ontology, and support analytics, operational workflows and AI applications for commercial and government customers, often under strict security and deployment constraints. Its students page distinguishes Software Engineers in product development from Forward Deployed Software Engineers, who work toward specific customers’ technical and operational outcomes. Relevant engineering areas include data integration and modeling, backend and distributed services, access control, frontend applications and deployment across varied environments.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Distributed systems engineering, and more

  Partial: no verified loop3 sources

• Snowflake

  Snowflake runs a cloud data platform that stores and queries large volumes of structured and semi-structured data on the major public clouds, with storage separated from elastically scaled compute. Engineering work spans the SQL engine (query optimization and execution, columnar storage, transactions and metadata), distributed services that provision and isolate compute, cloud infrastructure and reliability, security and governance, and AI/ML features that run close to customer data. Database internals and distributed-systems depth are therefore unusually relevant next to general coding skill.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Official guidance2 sources

• Stripe

  Stripe provides payments and financial infrastructure to businesses, mostly through developer-facing APIs: payment acceptance, billing and subscriptions, payouts and money movement, fraud prevention, tax and reporting. Engineering emphasizes API design with long-lived backward compatibility, correctness and idempotency for operations that move money, highly available distributed services, data pipelines, protection of sensitive credentials, and frontend and mobile components such as embeddable payment UIs and dashboards.

  Relevant roles: General software engineering, Backend engineering, Frontend / full-stack engineering, Distributed systems engineering, and more

  Historical guidance1 source

• Two Sigma

  Two Sigma is a technology-driven investment manager that applies data science and engineering to investing. Engineering work includes large-scale data platforms and ingestion, research and modeling infrastructure on distributed compute, trading systems, and tools for researchers. Its SWE interview guide lists C, C++, Java and Python as interview languages and spans data structures, algorithms, object-oriented design, concurrency and system design.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Official guidance1 source

• Uber

  Uber runs real-time marketplaces for rides, delivery and freight that match supply and demand across many cities. Engineering spans high-throughput backend services (dispatch and matching, pricing, payments), geospatial computation such as maps and arrival-time estimates, large data and streaming platforms, machine-learning infrastructure, and mobile apps that must work reliably across devices and network conditions.

  Relevant roles: General software engineering, Backend engineering, Distributed systems engineering, Infrastructure / platform engineering, and more

  Historical guidance2 sources