---
title: 'Software Engineer, ML Developer Experience at Anyscale'
canonical: 'https://feeny.ai/job/software-engineer-ml-developer-experience-anyscale-san-francisco-5htsk54j4ngf'
type: 'job'
last_seen: '2026-09-09'
---

# Software Engineer, ML Developer Experience at Anyscale

- **Company:** Anyscale
- **Location:** San Francisco, CA
- **Compensation:** $226k–$283k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-26
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/anyscale/81c3c26a-71e3-4c4c-a88e-88c538a169be

## 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, Cruise https://www.youtube.com/watch?v=gj0BqvfX_wI, 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 Software Engineer to join the ML Developer Experience (MLDevX) team. MLDevX owns the experience layer of the Anyscale platform: the interfaces through which users and coding agents discover, configure, run, observe, debug, and productionize AI workloads. Every user journey crosses this layer through the CLI, SDKs, APIs, UI, Workspaces, MCP, or the workflows and integrations built on top of them. Together, these form the user’s primary interface into Anyscale, turning distributed computing from a systems problem back into a coding problem. We build the common contracts, tools, control-plane services, and architecture that power these surfaces.

You will work across the stack from developer tooling to cloud infrastructure and the Ray runtime. Manage long-running operations and make failures across jobs, tasks, actors, nodes, and GPUs easier to diagnose. The systems you build must scale with the platform, remain predictable through failures, and be intuitive for developers, programmable for applications, and operable by coding agents.

This is a high impact individual-contributor role with end-to-end ownership. You will work directly with users and field teams to identify high leverage problems, shape the product and technical design, and build and operate the solution. The scope spans the AI workload loop - data preparation, fine-tuning and post-training, serving, evaluation, and iteration as well as the developer loop: code, submit, monitor, debug, optimize, and re-submit. We are looking for someone with strong product judgment, a willingness to understand the user base, and the technical depth to build high quality software for everyone from a developer learning Ray for the first time to an AI-native company or enterprise running production workloads at scale.

A SNAPSHOT OF PROJECTS YOU MAY WORK ON

- Build the next generation of developer tooling and MLOps capabilities on Ray, designed for both developers and coding agents.
- Develop an agent-first CLI and cohesive SDK, API, and MCP surfaces with self-discovery, structured errors, dry-run support, and consistent behavior across platform resources.
- Work across the Anyscale Workspaces stack to improve the path from local code to distributed execution, including environments, dependencies, images, authentication, workload submission, and debugging.
- Build cohesive experience, tools and frameworks for the AI development lifecycle, including data preparation, fine-tuning and post-training, evaluation, production serving, dataset management, experiment tracking, and lineage.
- Build the path from a trained model to a reliable production endpoint, including model registration, deployment workflows, performance benchmarking, and LLM-specific service metrics.
- Surface observability across the CLI, SDK, UI, and agent-facing interfaces so users can diagnose failures across jobs, tasks, actors, nodes, and GPUs.
- Design open integrations using durable standards such as OpenAI-compatible APIs and OpenTelemetry, along with stable Jobs and Services interfaces for external orchestrators.
- Design and operate the highly available backend services and platform architecture that power these capabilities across serverless and bring-your-own-cloud environments.
- Work closely with users and field teams to scope, ship, and iterate on the product, and collaborate with distributed systems and machine learning experts to push the boundaries of AI infrastructure.

WE'D LOVE TO HEAR FROM YOU IF YOU HAVE

- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 5+ years of experience writing high-quality production code
- A solid background in algorithms, data structures, and system design
- Experience working with modern machine learning tooling — PyTorch, MLflow, data catalogs, and similar
- Hands-on experience building and operating highly available services in production
- Strong product instincts and a track record of shipping developer-facing tools that people choose to use

## BONUS POINTS IF YOU HAVE

- Experience building and maintaining open-source projects
- Experience building and operating machine learning infrastructure in production
- Experience building highly available serving systems
- Experience using Ray

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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