---
title: 'Site Reliability Engineer, Platform Infrastructure (Foundations) at Anyscale'
canonical: 'https://feeny.ai/job/site-reliability-engineer-platform-infrastructure-foundations-anyscale-san-qc9t0scbmk32'
type: 'job'
last_seen: '2026-09-09'
---

# Site Reliability Engineer, Platform Infrastructure (Foundations) at Anyscale

- **Company:** Anyscale
- **Location:** San Francisco, CA
- **Compensation:** $200k–$240k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-26
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/anyscale/23733eb9-f839-4209-b191-36cb0ff5b973

## 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:

Anyscale is looking for a Site Reliability Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision.

Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads.

We are seeking a talented engineers with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale’s cloud platform.

You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers.

A snapshot of projects you may work on

- Design, build, and scale services that orchestrate Ray clusters across cloud and on-prem environments, supporting both VM-based and Kubernetes-based deployments
- Optimize control plane components for large-scale, distributed AI/ML workloads
- Build intelligent scheduling and resource management systems for heterogeneous compute clusters
- Develop features to enhance the reliability, performance, scalability, and observability of Anyscale-managed Ray workloads
- Support and optimize accelerator integration (e.g., GPUs, TPUs).
- Handle container image management and dependency resolution for distributed workloads
- Participate in code reviews, design and architecture discussions
- Provide on-call support, working closely with customer and field teams to troubleshoot infrastructure issues
- Collaborate with leading distributed systems and machine learning experts to push the boundaries of AI infrastructure

We'd love to hear from you if have

- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 3+ years of experience writing high-quality production code
- Hands-on experience in building and maintaining highly available, scalable, and performant distributed system
- Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments
- Deep understanding of networking, security, and authentication mechanisms in cloud environment
- Familiarity with observability stacks (Prometheus, Grafana etc)
- Proficiency in Go and Python
- Knowledge of low-level operating system foundations (Linux kernel, file systems, containers)

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 https://drive.google.com/file/d/1Kt2S6_k_SjxaEdGowH4rngVdg2ApAQV3/view?usp=sharing and the Right to Work posters in English and Spanish https://drive.google.com/file/d/1K3Nz72xgsU2hngnVUEu53wEeZjbAMbnZ/view?usp=sharing

## 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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