Software Engineer Distributed Systems Jobs

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

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Anyscale is looking for a Software Engineer to join the ML Developer Experience (MLDevX) team. MLDevX owns the experience layer of the Anyscale platform: the interfaces through which users and coding agents discover, configure, run, observe, debug, and productionize AI workloads. Every user journey crosses this layer through the CLI, SDKs, APIs, UI, Workspaces, MCP, or the workflows and integrations built on top of them. Together, these form the user’s primary interface into Anyscale, turning distributed computing from a systems problem back into a coding problem. We build the common contracts, tools, control-plane services, and architecture that power these surfaces. You will work across the stack from developer tooling to cloud infrastructure and the Ray runtime. Manage long-running operations and make failures across jobs, tasks, actors, nodes, and GPUs easier to diagnose. The systems you build must scale with the platform, remain predictable through failures, and be intuitive for developers, programmable for applications, and operable by coding agents. This is a high impact individual-contributor role with end-to-end ownership. You will work directly with users and field teams to identify high

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: As a Site Reliability Engineer, you will play a crucial role in ensuring the smooth operation of all user-facing services and other Anyscale production systems. Anyscale values diversity and inclusion, and we encourage applications from individuals of all backgrounds. This includes processes for provisioning, negotiating prices, managing costs, seeing opportunities for teams to reduce wastage by finding applications across the company. You will apply sound engineering principles, operational discipline, and mature automation to our environments and the Anyscale codebase as we scale. As part of this role, you will: Develop a unified perspective on how cloud components are utilized across the company, taking into account diverse needs and requirements. Ensure that deployment methodologies align with the company's reliability goals. Build systems that promote understanding of production environments, facilitating quick identification of issues through robust observability infrastructure for metrics, logging, and tracing. Create monitoring and alerting systems at different levels, enabling teams to easily contribute and enhance the overall monitoring capabilities. Establish testing infrastructure to s

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

About Anyscale: At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Anyscale is looking for a Software Engineer to join the Platform and Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the team, we build the scalable, secure, and robust backbone that enables this vision, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented Software Engineer with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale's cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impa

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: Optimizing performance of large-scale workloads on Ray Stability and stress testing infrastructure Improving fault tolerance (HA) As part of this role, you will: Leading cross-team projects while mentoring junior team members Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Ray aims to provide a universal API for building distributed applications (e.g. a machine learning pipeline of feature engineering, model training, and evaluation). Data is usually a core element connecting these different stages, and therefore plays a critical role in Ray’s usability, performance, and stability. We are looking for strong engineers to build, optimize, and scale Ray’s Datasets library and data processing capabilities in general. About the Ray Data team: The Ray Data team currently develops and maintains the Ray Datasets library, which is already powering critical production use cases (e.g. large scale data compaction at Amazon , and ML pipeline at Alibaba ). Ray Datasets is a Python library built on top of Apache Arrow and Ray Core (Ray’s C++ backend), and the Ray Data team interacts closely with Ray Core components including the scheduler and the memory & I/O subsystems. The Ray Data team also works closely with Ray’s ML libraries including Train, RLlib, and Serve. A snapshot of projects you will work on: - Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.) - Integration with ML training and data sources - Stability an

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: - Optimizing performance of large-scale workloads on Ray - Stability and stress testing infrastructure - Improving fault tolerance (HA) As part of this role, you will: Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements to Ray core Improve the testing process for Ray to make re

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Anyscale is looking for a Software Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented Software Engineer with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale’s cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers. A snapshot of projects you may work on Design, build, and scale services that orches

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: We are seeking talented distributed systems engineers who are passionate about building innovative solutions for application deployment. Your mission will be to enhance the capabilities of Replit Infrastructure, optimize performance across global regions, and drive efficiency while delivering an exceptional user experience. If you have a strong foundation in software development, a deep understanding of cloud technologies, and a track record of delivering high-quality code, we want to hear from you. In this role you will: Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services. Required skills and experience: Distributed systems: Track record of working with platform-as-a-service, distributed storage, o

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. Senior Software Engineer, Backend About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Robinhood’s engineering organization spans Crypto, Brokerage, and Core Engineering, each responsible for systems that are foundational to how customers invest and manage their money! These teams build and operate platforms for trading, custody, ledgers, reporting, payments, and shared infrastructure, with a strong focus on correctness, reliability, and customer trust. Engineers partner closely with product, design, data, and infrastructure teams to deliver software that performs at scale. As a Senior Software Engineer, you will design and build large-scale distributed systems that support real-time trading, balances, and platform capabilities. You will lead technically complex projects, contribute to architectural decisions, and collaborate with frontend and data partners to deliver well-structured APIs. Your work will directly influence system performance, operational safety, and long-term maintainability across core Robinhood products. This role is based in our Menlo Park, CA and New York, NY offices, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress,

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an