---
title: 'Staff Software Engineer, Ray Core at Anyscale'
canonical: 'https://feeny.ai/job/staff-software-engineer-ray-core-anyscale-san-francisco-5nag5yvmhcw4'
type: 'job'
last_seen: '2026-09-23'
---

# Staff Software Engineer, Ray Core at Anyscale

- **Company:** Anyscale
- **Location:** San Francisco, CA
- **Compensation:** $240k–$270k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-17
- **Last confirmed live:** 2026-09-23
- **Apply:** https://jobs.ashbyhq.com/anyscale/5f4d4f60-e8b8-4e03-a709-0117b3e7d48e

## 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.

## What you'll do

- Own a major technical area of Ray Core end to end, defining the roadmap, identifying the most important technical problems, and driving execution through production.
- Lead large, technically complex projects spanning multiple engineers, teams, and/or organizations.
- Set technical direction and make architectural decisions for distributed computing infrastructure used by demanding production workloads.
- Design, build, and evolve core distributed-systems primitives rather than simply integrating existing platforms or frameworks.
- Work on problems involving areas such as distributed execution, scheduling, resource management, fault tolerance, concurrency, networking, storage, or system performance.
- Stay hands-on with implementation and debugging in a systems-oriented codebase, while raising the technical bar for the engineers around you.
- Help shape the longer-term architecture and evolution of Ray Core as our workloads and scale continue to grow.

## What we're looking for

- 6+ years of software engineering experience, with a track record of increasing technical ownership.
- Experience leading substantial projects end to end, including defining the problem, creating a roadmap, making architectural decisions, driving implementation, and owning the outcome in production.
- Experience leading projects that are larger than a single-engineer effort, typically spanning multiple engineers and lasting multiple quarters.
- Deep experience with distributed systems and computer systems.
- Strong systems programming experience in languages such as C++, Rust, Java, or similar lower-level languages.
- Strong understanding of systems concepts such as multithreading/concurrency, distributed coordination, resource management, fault tolerance, performance, or networking.
- Experience building foundational systems such as databases, streaming systems, distributed runtimes, operating systems, schedulers, storage systems, Spark, Kafka, or similar infrastructure is highly relevant.
- A track record of mentoring engineers and raising the technical bar of the teams around you.
- Nice to have: Contributions to open-source infrastructure projects.

## 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.

## 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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