Software Engineer, Ray Data

Reposted 22 Days Ago
Be an Early Applicant
Bengaluru, Karnataka, IND
In-Office
5-5 Annually
Senior level
Artificial Intelligence • Software
The Role
Develop high-quality software for distributed programming, optimize Ray's Datasets library, and improve testing processes. Communicate work through tutorials and talks.
Summary Generated by Built In

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 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:

- Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.)

- Integration with ML training and data sources

- Stability and stress testing infrastructure

- Lead future work integrating streaming workloads into Ray such as Beam on Ray

- Differentiate Data operations in Anyscale hosted Ray service

As part of this role, you will:

  • Develop high quality open source software to simplify distributed programming (Ray)

  • Identify, implement, and evaluate architectural improvements to Ray core and Datasets

  • Improve the testing process for Ray to make releases as smooth as possible

  • Communicate your work to a broader audience through talks, tutorials, and blog posts

We'd love to hear from you if have:

  • At least 5 years of relevant work experience

  • Solid background in algorithms, data structures, system design

  • Experience in building scalable and fault-tolerant distributed systems

  • Experience with data processing, database internals including Spark or Dask (streaming is a plus)

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

Skills Required

  • At least 5 years of relevant work experience
  • Solid background in algorithms, data structures, system design
  • Experience in building scalable and fault-tolerant distributed systems
  • Experience with data processing, database internals including Spark or Dask

Anyscale Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anyscale and has not been reviewed or approved by Anyscale.

  • Fair & Transparent Compensation Pay is considered market-based with target ranges shown in postings and a stated market-based philosophy. Feedback suggests this clarity and consistency aid confidence in pay fairness.
  • Equity Value & Accessibility Equity is commonly included in offers and is positioned as a meaningful part of total compensation for many roles. Feedback suggests this equity participation enhances perceived overall pay competitiveness.
  • Healthcare Strength Health, dental, and vision coverage are described as robust with many plan options, alongside mental-health support and fertility benefits. Feedback suggests this strong core healthcare offering increases perceived benefits quality.

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The Company
HQ: San Francisco, CA
115 Employees
Year Founded: 2019

What We Do

Distributed computing made simple Anyscale enables developers of all skill levels to easily build applications that run at any scale, from a laptop to a data center.

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