Anyscale
Software Engineer (Ray Data)
About this role
Anyscale is hiring a Software Engineer to develop and optimize Ray Data, a Python-native distributed data processing engine for AI/ML workloads. You'll improve performance for batch inference, ensure efficient pipeline scaling, and work directly with customers deploying large-scale AI applications.
What you'll do
- Optimize Ray Data performance for multi-modal batch inference and complex AI workloads
- Design efficient data pipeline scaling across heterogeneous environments
- Build data loading solutions for production training workloads
- Improve stability and fault tolerance at high scale
- Collaborate with customers to scale their AI workloads using Ray Data
- Develop and maintain core Ray Data functionality
What they're looking for
- Distributed systems design and implementation
- Python programming
- Data processing and pipeline architecture
- Database internals and query optimization
- Fault tolerance and reliability patterns
- Performance optimization at scale
- Large-scale system engineering
- Machine learning infrastructure
Benefits
- Work on open-source technology used by OpenAI, Uber, Spotify
- Impact AI/ML infrastructure at scale
- San Francisco-based role
- Backed by top-tier VCs (Andreessen Horowitz, NEA, Addition)
- Collaborative team focused on distributed computing
- Equal opportunity employer
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Anyscale
Anyscale builds Ray, an open-source distributed computing framework and enterprise platform for scaling AI workloads across Kubernetes and cloud providers. The company is hiring forward-deployed engineers to work embedded with customers, software engineers to develop Ray Core, LLM inference specialists, and customer support engineers who combine technical expertise with post-sale success.
- Website
- anyscale.com
Likely interview questions
- Describe your experience building or optimizing distributed data processing systems—what were the key performance bottlenecks you addressed?
- How have you approached fault tolerance and reliability in large-scale systems you've worked on?