---
title: 'Software Engineer, Ray Data at Anyscale'
canonical: 'https://feeny.ai/job/software-engineer-ray-data-anyscale-bengaluru-hwyxwsx70yjr'
type: 'job'
last_seen: '2026-10-14'
---

# Software Engineer, Ray Data at Anyscale

- **Company:** Anyscale
- **Location:** Bengaluru, India
- **Employment:** full-time
- **Posted:** 2026-07-28
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.ashbyhq.com/anyscale/2d76cfa2-f857-42b2-9c74-c07beca01458

## Job description

About Anyscale:

At [Anyscale](https://www.anyscale.com/), we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing [Ray](https://docs.ray.io/en/latest/), a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like [OpenAI](https://thenewstack.io/how-ray-a-distributed-ai-framework-helps-power-chatgpt/), [Uber](https://www.uber.com/blog/horovod-ray/), [Spotify](https://engineering.atspotify.com/2023/02/unleashing-ml-innovation-at-spotify-with-ray/), [Instacart](https://www.youtube.com/watch?v=3t26ucTy0Rs&list=PLzTswPQNepXmLUiL4F_1VHrPcCz1OeILw&index=23&pp=iAQB), [Cruise](https://www.youtube.com/watch?v=gj0BqvfX_wI&list=PLzTswPQNepXmLUiL4F_1VHrPcCz1OeILw&index=46&pp=iAQB), 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](https://www.wsj.com/articles/ai-startup-anyscale-adds-99-million-to-andressen-horowitz-led-funding-round-11661254200) 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](https://docs.ray.io/en/latest/data/dataset.html) library and data processing capabilities in general.

About the Ray Data team:

The Ray Data team currently develops and maintains the Ray [Datasets](https://docs.ray.io/en/latest/data/dataset.html) library, which is already powering critical production use cases (e.g. [large scale data compaction at Amazon](https://www.anyscale.com/events/2022/01/20/ray-meetup-is-back-in-the-new-year-2022), and [ML pipeline at Alibaba](https://www.anyscale.com/blog/building-an-end-to-end-ml-pipeline-using-mars-and-xgboost-on-ray)). 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](https://docs.ray.io/en/latest/data/dataset.html) 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.

## About Anyscale

## Company Overview
- **One-liner**: Anyscale provides a production-grade platform for building, running, and scaling data-intensive AI workloads, powered by the open-source Ray framework.
- **Entity Type**: Private (backed by prominent venture investors)
- **Headquarters**: San Francisco, CA, USA (600 Harrison Street, 4th Floor) and Bangalore, India
- **Founded**: 2019
- **Founders**: Co-founders include the creators of Ray from UC Berkeley RISELab (names not explicitly listed in provided sources)

## Core Business
- **Primary industry**: AI Infrastructure / Distributed Computing
- **Target customers**: AI teams building foundation models, data curation pipelines, batch inference, and serving workloads; B2B enterprise and startups
- **Mission**: Make scalable computing effortless  
  **Vision**: Build the future of distributed computing for AI and ML workflows

## Products & Services
- **[Anyscale Platform](https://www.anyscale.com/platform)**: A managed, production-grade platform that runs Ray clusters across any cloud. Includes developer tooling (Workspaces, managed dashboards), cluster orchestration (Jobs & Services, autoscaling, multi-cloud), governance (SSO, SAML, SCIM, budgets), observability (workload-specific dashboards, lineage tracking), and the fully managed Anyscale Runtime.
- **Ray Open-Source Framework**: Although open source and community-driven, Anyscale is built by the creators of Ray and offers the runtime as the core compute engine for its platform.

## Market Standing
- **Valuation/Market Cap**: Not disclosed in provided sources
- **Key Metric**: Total funding not specified in sources; investors include Sequoia Capital, Andreessen Horowitz, NEA, and others (based on investor logos on [about page](https://www.anyscale.com/about)). Ray has exceeded **500 million downloads** and **41K+ GitHub stars**.
- **Notable Investors/Partners**: Sequoia Capital, Andreessen Horowitz, NEA (from company website); partners include AWS, GCP, Azure, CoreWeave, Nebius.
- **Growth Signals**: Employee recommendation rating of **94%**; **4.7 Glassdoor** rating; three offices globally; used by foundation model builders for tasks like embedding generation (80% cheaper), batch inference (3x faster), and training (5x faster).

## Competitive Advantages
- **Ray ecosystem**: Anyscale is built and maintained by the original creators of Ray, the most widely adopted open-source AI compute engine, giving them deep technical expertise and influence on the project’s direction.
- **Multi-cloud orchestration**: Run workloads seamlessly across AWS, GCP, Azure, and specialized GPU clouds without cloud-specific rewrites.
- **Fine-grained hardware allocation and GPU pooling**: Dynamic capacity reallocation maximizes GPU utilization and reduces costs.
- **Developer experience**: Simple Python APIs (e.g., `@ray.remote`) and cluster-backed VS Code/Jupyter workspaces enable scaling from a laptop to a data center without code changes.

## Strategic Focus
- **Current priorities**: Foundation model training and post-training (RLHF, fine-tuning), multimodal data curation, batch embedding generation, and real-time serving. Emphasis on reducing GPU costs and improving developer velocity through unified governance and observability.
- **Direction for growth**: Expanding multi-cloud orchestration, deepening integrations with third-party libraries (vLLM, SGLang, PyTorch, XGBoost), and enabling teams to “unify and govern every team’s AI workloads across clouds.”

## Why Work Here
- **Culture**: Values include “Customer & Community Obsessed,” “LFG” (move fast, push boundaries), “Raise the Bar,” “Take the Longview.”
- **Remote/hybrid/office**: Offices in San Francisco, Palo Alto, and Bangalore. In-office meals (lunch and dinner) and commute reimbursement for Bay Area residents.
- **Benefits**:
  - Health, Vision, Dental (95% covered plans)
  - Fertility benefits (up to $12,500 via Kindbody) and 12 weeks paid parental leave
  - Flexible time off
  - $100/month learning and wellness stipend
  - Paid volunteer time off
  - Mental health support (Rula)
- **Engineering culture**: High autonomy, work on cutting-edge AI infrastructure, close connection to open-source community.

## Sources
1. [anyscale.com](https://www.anyscale.com/)
2. [anyscale.com/about](https://www.anyscale.com/about)
3. [anyscale.com/careers](https://www.anyscale.com/careers)
4. [anyscale.com/platform](https://www.anyscale.com/platform)
5. [jobs.ashbyhq.com/anyscale](https://jobs.ashbyhq.com/anyscale)

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