Forward Deployed Engineer - AI/ML Platforms
Anyscale · San Francisco
About this role
## Forward Deployed Engineer - AI/ML Platforms 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/), an open-source project powering scalable machine learning—used by teams including OpenAI, Uber, Spotify, Instacart, Cruise, and more. With Anyscale, we’re building the best place to run Ray so developers and data scientists can scale ML applications from their laptop to the cluster—without needing to be distributed systems experts. --- ### About the role As a **Forward Deployed Engineer - AI/ML Platforms** at Anyscale, you’ll partner with leading AI organizations to **design, deploy, and operate infrastructure** for production AI workloads. You’ll work closely with customer **platform, infrastructure, and ML engineering teams** to build scalable AI platforms, modernize ML infrastructure, and operationalize distributed AI applications on **Ray** and the **Anyscale platform**. You’ll serve as both a **trusted technical advisor** and a **hands-on engineer**, guiding customers from architecture and deployment through production operations—and providing feedback that directly shapes the evolution of the Anyscale platform. --- ### In this role, you will: - Design and implement **production-grade AI platform architectures** on **Kubernetes** and public cloud infrastructure (**AWS, Azure, GCP**) - Partner directly with customer platform, infrastructure, and ML engineering teams to **deploy, operate, and optimize** distributed AI workloads - Lead implementation engagements covering **installation, networking, security, observability, scaling, upgrades, and operational readiness** - Troubleshoot complex distributed systems issues across **infrastructure, Kubernetes, networking, storage, and AI applications** - Develop **automation, tooling, reference implementations, and infrastructure-as-code** to improve repeatability and accelerate customer success - Build trusted relationships with technical leaders and stakeholders, translating business objectives into robust technical solutions - Collaborate with **Product and Engineering** to communicate customer requirements and shape future platform capabilities - Share best practices through **documentation, architecture guidance, workshops, and enablement** --- ### We’d love to hear from you if you have: - **5+ years** of experience in cloud infrastructure, platform engineering, DevOps, SRE, or software engineering - Experience building, deploying, or operating **ML/AI platforms** for training, inference, or large-scale data processing - Strong expertise with **Kubernetes** and containerized production environments - Experience operating cloud infrastructure on **AWS, Azure, or GCP** (networking, security, IAM, storage, automation) - Experience with **Infrastructure as Code** and modern DevOps tooling such as **Terraform, Helm, GitOps, CI/CD**, or similar - Strong software engineering skills in **Python, Go, Java**, or a comparable language (automation/production services) - Experience working directly with **enterprise customers** in consulting, professional services, field engineering, solutions architecture, or similar - Excellent communication skills with the ability to work with both **executive** and **deeply technical** stakeholders - Familiarity with distributed computing frameworks such as **Ray, Spark, Dask**,
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