Staff Software Engineer, Ray Data
Anyscale is hiring a Staff Software Engineer, Ray Data in San Francisco, United States. It pays $240k-$270k a year and Level rates it ; you can apply on Anyscale.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts 43% higher than the typical software engineer posting on Level.
- The posting mentions OpenAI, Python and Ray among its tools and skills.
- Level classes it as a senior role.
- Anyscale has 20 other open roles on Level.
AI in this role
Design and scale Ray Data, the distributed data processing engine powering modern AI workloads and large-scale batch inference.
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 a Python-native data processing engine and a one-stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting-edge AI frameworks using both multimodal and structured data.
The Ray Data team develops and maintains Ray Data, building the underlying distributed data processing infrastructure that powers modern AI workloads. We are a team of engineers passionate about solving challenging problems in distributed systems, data processing, and performance at scale. We are looking for exceptional engineers to build, optimize, and scale Ray Data for increasingly complex AI workloads, including multimodal data processing and large-scale batch inference.
Learn more about how Ray Data enables scalable multimodal AI workloads in Architecting Multimodal Data Pipelines That Scale with Ray.
As part of this role, you will:
Design, build, and improve the core systems that power Ray Data, with a focus on performance, scalability, and reliability.
Design and optimize distributed execution across different stages of data pipelines in heterogeneous environments.
Build data loading and processing solutions for production training and inference workloads.
Solve challenging problems in distributed execution, scheduling, resource management, data partitioning, fault tolerance, and performance optimization.
Make system-level architectural decisions and reason through tradeoffs in areas such as resource allocation, execution models, batch vs. streaming workloads, and consistency and availability.
Work with customers and new-age AI-native companies to understand and solve challenges in scaling their AI workloads.
We'd love to hear from you if you have:
6+ years of experience building production-grade software, infrastructure, or developer-facing systems, with strong Python engineering experience.
6+ years of experience personally owning core architectural decisions within a distributed data or compute engine, rather than primarily operating or using a platform someone else designed.
Deep experience with distributed systems internals, such as scheduling, fault tolerance, data partitioning, distributed execution, performance optimization, or database and query engine internals.
A track record of reasoning through system-level tradeoffs and defending architectural decisions, such as batch vs. streaming, static vs. dynamic resource allocation, or consistency vs. availability.
Passion for solving the unsolved problems in large-scale AI infrastructure and building systems that enable the next generation of AI applications.
Why Anyscale
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
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish
How we rate this
Staff Software Engineer, Ray Data at Anyscale rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $240k
- Typical software engineer job
- $168k
This posting starts 43% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where data processing was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Walk me through how you've used OpenAI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Distributed Systems, Data Processing, Machine learning, Infrastructure, and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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