Staff Software Engineer, Ray Data

Anyscale; San Francisco, Northern (CA, KY); On-site; USD 170,000 - 260,000; Full time

Job summary

Anyscale is seeking exceptional engineers to design, build, and scale Ray Data, a Python-native data processing engine powering modern AI workloads. You will work on core systems, optimize distributed execution, and collaborate with customers to solve hard scalability challenges.

The role requires 6+ years of production-grade software experience with Python, deep knowledge of distributed systems, and a track record of architectural decision making in data or compute engines.

Qualifications

• 6+ years of production-grade software or infrastructure experience.
• Strong Python engineering experience.
• Experience owning architectural decisions in distributed data or compute engines.

Responsibilities

• Design, build, and optimize core Ray Data systems for performance and scalability.
• Work on distributed execution across data pipelines.
• Develop data loading and processing for training and inference workloads.
• Address fault tolerance, partitioning, and resource management.

Skills

Python

Distributed systems

Performance optimization

Scheduling

Tools

Ray

Linux

Docker

Job description

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