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Software Engineer (Ray Data)
Company | Anyscale |
Address | San Francisco, CA, United States |
Employment type | FULL_TIME |
Salary | |
Category | Software Development |
Expires | 2023-12-21 |
Posted at | 10 months ago |
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.
We're a San Francisco based company, proud to be backed by $250+ million from top-tier investors like Andreessen Horowitz, NEA, and Addition .
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
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.
We're a San Francisco based company, proud to be backed by $250+ million from top-tier investors like Andreessen Horowitz, NEA, and Addition .
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
- Stability and stress testing infrastructure
- Lead future work integrating streaming workloads into Ray such as Beam on Ray
- Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.)
- Differentiate Data operations in Anyscale hosted Ray service
- Integration with ML training and data sources
- Improve the testing process for Ray to make releases as smooth as possible
- Identify, implement, and evaluate architectural improvements to Ray core and Datasets
- Develop high quality open source software to simplify distributed programming (Ray)
- Communicate your work to a broader audience through talks, tutorials, and blog posts
- Experience with data processing, database internals including Spark or Dask (streaming is a plus)
- Experience in building scalable and fault-tolerant distributed systems
- At least 2 year of relevant work experience
- Solid background in algorithms, data structures, system design
- 401k Retirement Plan
- Wellness stipend
- Healthcare plans, with premiums covered by Anyscale at 99%
- Stock Options
- 100% of in office meals covered
- This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including the following:
- Education stipend
- Flexible Time Off
- Paid Parental Leave
- At Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent. The target salary for this role is $170,112 ~ $237,000. As the market data changes over time, the target salary for this role may be adjusted.
- Commute reimbursement
-
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