СШАStaff Software Engineer, Ray Core
4 нед. назад
220k–250k USD / годСШАLeadHybrid
distributed-systemsschedulingresource-managementfault-toleranceconcurrencynetworkingstorage
Lead major technical projects and define roadmap for distributed computing infrastructure of Ray Core to support scalable machine learning applications.
О компании
- At , 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 , 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.
Требования
- 6+ years of software engineering experience, with a track record of increasing technical ownership.
- Experience leading substantial projects end to end, including defining the problem, creating a roadmap, making architectural decisions, driving implementation, and owning the outcome in production.
- Experience leading projects that are larger than a single-engineer effort, typically spanning multiple engineers and lasting multiple quarters.
- Deep experience with distributed systems and computer systems—not primarily using existing distributed platforms.
- Strong systems programming experience in languages such as C++, Rust, Java, or similar lower-level languages.
- Strong understanding of systems concepts such as multithreading/concurrency, distributed coordination, resource management, fault tolerance, performance, or networking.
- Experience working on systems such as databases, streaming systems, distributed runtimes, operating systems, schedulers, storage systems, Spark, Kafka, or similar infrastructure is highly relevant.
- A track record of mentoring engineers and raising the technical bar of the teams around you.
- Nice to have: Contributions to open-source infrastructure projects.
Другое
- Own a major technical area of Ray Core end to end, defining the roadmap, identifying the most important technical problems, and driving execution through production.
- Lead large, technically complex projects spanning multiple engineers, teams, and/or organizations.
- Set technical direction and make architectural decisions for distributed computing infrastructure used by demanding production workloads.
- Design, build, and evolve core distributed-systems primitives rather than simply integrating existing platforms or frameworks.
- Work on problems involving areas such as distributed execution, scheduling, resource management, fault tolerance, concurrency, networking, storage, or system performance.
- Stay hands-on with implementation and debugging in a systems-oriented codebase, while raising the technical bar for the engineers around you.
- Help shape the longer-term architecture and evolution of Ray Core as our workloads and scale continue to grow.
- We're on a mission to make scalable computing effortless. Ray is the AI Compute Engine at the center of some of the world's most powerful AI platforms
- Our tech is in production at companies like OpenAI, Uber, Spotify, Instacart, and Cruise
- We're backed by Andreessen Horowitz, NEA, and Addition, with $250M+ raised to date
- Recent partnerships with Azure, CoreWeave, and Google Cloud are putting AI-native compute directly into enterprise environments
- Competitive salary and equity, plus health/dental/vision coverage (many plans up to 99% employer-covered)
- We offer flexible time off, paid parental leave, and mental health support